Process Description
P-Value Quantile Plotter
Welcome to JMP Genomics |
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Getting Started with JMP Genomics |
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System Requirements |
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Text Conventions |
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The Genomics Main Menus |
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The File Menu |
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The Genomics Starter |
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Important Differences between JMP and JMP Genomics Dialogs |
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Running a Process |
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Tabbed Reports |
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Stopping a Process |
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Saving and Loading Settings |
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SAS Variable Names and Labels |
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Files and Data Sets |
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SAS Data Sets |
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Experimental Design File (EDF) |
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Data Sets Used in JMP Genomics Processes |
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Sample Case Studies |
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The JMP Genomics Starter |
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Current Study |
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Studies |
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Import |
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Experimental Design File |
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Affymetrix |
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Illumina |
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Nanostring |
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Other Expression |
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Other Genetics |
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Proteomics |
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Next-Gen Sequencing |
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Text |
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Summarize |
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Workflows |
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Basic |
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Advanced |
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Genetics |
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Genetics Utilities |
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Relatedness Measures |
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Genetic Marker Statistics |
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GWAS Testing |
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Other Association Testing |
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Haplotype Analysis |
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Model-free Linkage |
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Linkage Maps and QTL |
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Breeding Analysis |
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Copy Number |
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Spectral Preprocessing |
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Expression |
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Quality Control |
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Normalization |
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Normalization (Next-Gen) |
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Differential Expression |
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Expression Utilities |
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Pattern Discovery |
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Predictive Modeling |
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Main Methods |
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Model Comparisons |
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Predictive Modeling Utilities |
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Subgroup Analysis |
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P-Value Operations |
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Genome Views |
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Genome Browser |
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Track Creation |
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Annotation Analysis |
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General |
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Affymetrix |
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Ingenuity |
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GSEA / MSigDB |
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SAS Data Set Utilities |
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Tables |
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Rows |
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Columns |
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Import/Export |
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General Utilities |
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Documentation and Help |
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The Menu Bar |
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Add Study |
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Manage Genomics Studies |
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View Study Metadata |
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Assign Default Data Sets |
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Assign Wide Variable Roles |
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Imputed SNP Import Tutorial |
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Basic Genetics Workflow |
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Basic Linkage Mapping Workflow |
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Basic Copy Number Workflow |
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Basic Exon/Alternative Splicing Workflow |
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Basic Expression Workflow |
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Basic miRNA/miRNA-Seq Workflow |
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Basic RNA-Seq Workflow |
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Basic Tiling Workflow |
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Genetics Rare Variants Workflow |
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Genetics Q-K Analysis Workflow |
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Expression QC Workflow |
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Expression Statistics Workflow |
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Workflow Builder |
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Journal Builder |
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Variable Gene Selection |
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Evaluation of Normalization Methods |
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Introduction to Predictive Modeling |
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Customize Genomics Starter |
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Register Add-ins |
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R Package Manager |
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Generate Genomics Dialogs |
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JMP Genomics Programming Guide |
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Getting Started |
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The Column Contents Process |
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The Anatomy of a JMP Genomics Analytical Process |
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Adding and Deleting JMP Genomics Analytical Processes |
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JMP Genomics XML Tags, Attributes, and Values |
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The Column Contents Process |
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JMP Genomics XML tags, Attributes, and Values |
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Symbols |
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Writing your XML Code |
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Example: A Process for Creating a SAS Data Set |
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The Import Individual Text, CSV or Excel Files Process |
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SAS Code for the Import Individual Text, CSV, or Excel Files Process |
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XML Code for the Import Individual Text, CSV, or Excel Files Process |
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Creating a JSL File for Dynamic Graphics and Analyses |
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The Distribution Analysis Process |
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SAS Code for Generating JSL |
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Macros Available for JMP Genomics Processes |
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Macro Descriptions |
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Writing High Quality Processes |
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Audience |
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Development Tips |
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Code Reuse |
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Improving Your SAS Macro Language Skills |
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Line and Macro Length Limits |
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Additional Resources |
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Introduction |
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AceView Database |
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Annotation Summary |
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Change Significance Criterion |
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Check Variable Requirement and Usage |
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Close All |
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Cluster Domains |
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Construct One-way Plots |
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Contingency |
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Contingency Analysis |
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Create Subset Experimental Design Data Set |
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Create Subset Experimental Design Data Set, Excluding Selected Curves |
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Create Subset Genotype and Annotation Data Sets |
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Create Subset with Mean Difference and P-value Criteria |
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dbSNP |
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Describe Output |
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Dot Plot |
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Enter new -log10(p) cutoff |
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Entrez Cross |
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Entrez Gene |
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Exclude Markers and Rerun Analysis |
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Fit Incidence Density Model |
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Fit Model and Plot LS Means |
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Fit Survival Model to Input Data for Selected Rows |
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Forest Plot |
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Forest Plots of Credible Intervals |
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GenBank Nucleotide |
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Gene List |
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Generate Report |
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Genotype |
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GO Stat |
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Graph Time Trends |
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Graph Trellis Plot |
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IPA Upload |
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iPathwayGuide Output Data |
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Launch Interactive LD Plots for R^2 |
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Launch JMP Genomics Browser |
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Launch Plot Intensities |
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Linkage Group X |
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Malecot LD Map |
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Odds Ratio Plot |
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Onto-Express |
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Open Subset in Tall Format |
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Open Subset in Wide Format |
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Partial Correlation Diagram |
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Plot Fixed Effect Components |
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Plot Oneway Means by Chromosome Position and Overlay Tracks |
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Plot Survival Curves for Stratified Data |
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Plot Trait by Genotype |
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PubMed |
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Reopen Dialog |
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Reverse Linkage Group Marker Orders |
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Revert Clustering |
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Save Current Linkage Group Membership |
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Select Markers in Graphs or Linked Tables, then Click to View Survival Curves |
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Show Duplicates |
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Show Rows in Heat Map |
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Subset and Transpose |
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Autocorrelation Plot |
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Bar Chart |
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Box Plot |
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Bubble Plot |
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Cell Plot |
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Chart |
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Contingency Plot |
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Contingency Table |
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Contour Plot |
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Correlogram |
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Dendrogram |
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Distance Graph |
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Distribution |
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Forest Plot |
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Geographical Map |
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Hazard Ratio Event Plot |
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Heat Map and Dendrogram |
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Histogram |
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LD Decay Plot |
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MA Plot |
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Manhattan Plot |
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Matched Pairs Analysis |
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Mosaic Plot |
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One-way Plot |
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Overlay Plot |
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Parallel Plot |
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Principal Components Analysis Plot |
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Q-Q Plot |
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Receiver Operating Characteristics (ROC) Curves |
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Reliability Diagram |
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Scatterplot |
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Scree Plot |
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Segmentation Summary Plot |
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Shift Plot |
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Standardized Residual Plots |
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Surface Plot |
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Survival Curves |
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Survival Plot |
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Time Series Graph |
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Trace Plot |
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Tree Map |
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Trellis Plot |
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Volcano Plot |
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Waterfall Plot |
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Annotation Data Sets |
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Combine this Study with Study from Update Tab |
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Combine with: |
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Combined Study Name |
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Default Annotation Data Set |
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Default Wide Input Data Set |
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Default Experimental Design Data Set |
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Default Tall Input Data Set |
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Delete study |
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Dependent Variable |
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Experimental Design Data Sets |
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Folder of Annotation Study Data Sets |
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Folder of Experimental Design Study Data Sets |
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Folder of Tall Study Data Sets |
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Folder of Wide Study Data Sets |
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Input SAS Data Set |
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Label Variable |
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List-Style Specification of Lock-In Categorical Predictor Variables |
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List-Style Specification of Lock-In Class Predictor Variables |
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List-Style Specification of Lock-In Continuous Predictor Variables |
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List-Style Specification of Predictor Categorical Variables |
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List-Style Specification of Predictor Continuous Variables |
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Lock-In Categorical Predictor Variables |
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Lock-In Class Predictor Variables |
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Lock-In Continuous Predictor Variables |
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New Study Name |
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Output Folder |
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Predictor Categorical Variables |
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Predictor Continuous Variables |
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Server Output Directory |
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Study |
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Study Name |
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Tall Data Sets |
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Wide Data Sets |
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Weight Variable |
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UNNAMED (Blank is a delimiter) |
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UNNAMED (Parse from left) |
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Additional New Design Variable Names |
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Affection Status Coding |
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Allele Delimiter |
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Allele Peaks Data Set |
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Alleles to Use for Genotypes |
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Allocate Memory Size |
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Alternate Phenotype File |
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Annotated Variants within Known Genes (gene) |
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Annotation Columns |
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Annotation Data Set |
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Annotation File |
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Annotation Gene Name Variable |
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Annotation Merge Variables |
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Annotation SAS Data Set |
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Apply log2 transformation to intensities |
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Apply original column names |
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ArrayTrack Annotation Output Data Set |
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ASM Files from Version of Assembly Pipeline prior to 2.0 |
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Background Correction |
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Background Correction Method |
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Background Subtraction |
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Barcode File to Import |
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Baseline Reference Data Set |
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Baseline Reference SAS Data Set |
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Baseline Variable |
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BIM File |
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Bin Method |
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Bin Size |
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Bin Summary Statistic |
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Binary PED File |
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Binding Density QC |
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By Variables |
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Cast Selected Columns into Roles |
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Cel Layout File |
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CGA Tools testvariants File |
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Channel Status |
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Check available disk space |
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Check uniqueness of column names |
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Choose a folder containing files listed in the File column |
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Chromosome |
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Chromosome Summary Data Set |
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Chromosome Variable |
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CN Columns to Include |
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CN Measurements to Include (100K or 500K Arrays) |
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Code genotypes numerically |
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Column Delimiter |
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Column Delimiter for Genotype Probability File(s) |
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Columns to Include |
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Columns to Include In Output Data Set |
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Combine multiple VCF files into a single data set |
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Compress output data sets |
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Compute Reference Scaling Factor |
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Continuous Variables to Summarize |
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Control Gene Normalization |
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Copy Number Annotation Data Set |
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Copy Number Annotation SAS Data Set |
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Copy Number Data Set |
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Copy Number File |
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Count Data |
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Count of Variations by Gene (geneVarSummary) |
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Count reads by strand |
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Covariate File |
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Covariate File has a Header Row |
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Create Combined Data Set |
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Create Quality Flag Data Set |
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Create separate data sets for B_Allele_Freq and/or Log_R_Ratio |
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Create separate data set(s) for each chromosome when there are more variants than: |
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Create separate data sets for each selected measurement |
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Create separate data sets for SNP- and CN-summarized probesets |
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Create wide Output Genotype Data Sets |
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Cross Type |
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Custom File Filter Expression |
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Customer Array |
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Cut-off for DP |
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Cut-off for GQ |
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Data File |
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To Specify a Data File Type: |
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Data Set Containing Probes to Remove |
|
Data Start Row |
|
Data Step Statements |
|
Delimiters |
|
Detection p-Value Cutoff for Setting Individual Intensities to Missing |
|
Display marker genotype cell color plots |
|
Drop SNPs with this percentage of samples that are below: |
|
Encoding of Raw Array Files |
|
End |
|
Exclude rows with missing physical position |
|
Exon Count |
|
Exon Ends |
|
Exon Starts |
|
Experimental Design Data Set Corresponding to Baseline Reference Data Set |
|
Experimental Design File |
|
Experimental Design SAS Data Set Corresponding to Baseline Reference SAS Data Set |
|
Exponential Multiplier of Kernel Density |
|
Expression |
|
FAM File |
|
Feature Identifier |
|
Feature Identifier for Computing Counts |
|
File Filter Expression |
|
File Type |
|
Files for Variants Call |
|
Files in PBAT Format |
|
Filter before: |
|
Filter out genes with detection p-value above: |
|
Filter to Exclude Chromosomes |
|
Filter to Include Chromosomes |
|
Filter to Include Annotation Rows |
|
Filter to Include Gene Model Rows |
|
Filter to Include Markers |
|
Filter to Include Observations |
|
Flag Filter Expression |
|
Folder Containing a FASTA-formatted Reference Sequence |
|
Folder Containing Other Library Files |
|
Folder Containing Raw Data Files |
|
Folder Containing Raw Sequence Files |
|
Folder Containing Rterm.exe |
|
Folder Containing the BPMAP Files |
|
Folder Containing the CDF File |
|
Folder Containing the Library Files |
|
Folder Containing the Meta Probeset File |
|
Folder Containing the RCC Data Files |
|
Folder of BAM Files |
|
Package or Individual Genome Folder Containing ASM Results |
|
Folder of Data Files from Eland |
|
Folder of Feature-Barcode Matrices |
|
Folder of Illumina Data File |
|
Folder of Input Files |
|
Folder of Raw Array Files |
|
Folder of Raw BAM Data Files |
|
Folder of Raw Data Files |
|
Folder of Raw Files |
|
Folder of Raw SAM Data Files |
|
Folder of Samples File |
|
Folder of SNP/DIP Detection Table CSV Files |
|
Folder of Track Gene Text Settings Files |
|
Folder of VCF Files |
|
...for at least this percentage of the samples |
|
GC Score Cutoff |
|
Gene File to Import |
|
Gene Identifier |
|
Gene Model Text File |
|
Genotype Data Set |
|
Genotyping Error Threshold |
|
Genotype File |
|
Genotype Files |
|
Genotype Probability File(s) |
|
Genotype Probability Threshold |
|
Genotyping Calls Data Set |
|
Get all column names from first row |
|
Get Breadth of Coverage |
|
Housekeeping Genes |
|
How shall I get the information about your experiment |
|
ID Variables |
|
ID Variables to Keep |
|
Illumina Data File |
|
Imaging QC |
|
Import CEL intensities without merging annotation |
|
Include intron bins |
|
Include MM in output |
|
Include sequence data in output |
|
Include SNP variants only |
|
Increase R Software Memory Limit |
|
Indicator of Different Column Names across Raw Data Files |
|
Individual Variables |
|
Input Arlequin File |
|
Input Data Set |
|
Input NEXUS File |
|
Input OneMap File |
|
Input Pedigree File |
|
Input Phenotype File |
|
Input SAS Data Set |
|
Input SAS Data Set |
|
Input WinQTLCart File |
|
Intensity Variables to Bin |
|
Keep single probes not associated to any probeset |
|
Keep single-probe-sets not associated to any transcript cluster |
|
Key Variable(s) to Merge with Input Data Set |
|
Key Variable(s) to Merge with Input SAS Data Set |
|
Length of Sample ID Column |
|
LGEN File |
|
List of Phenotype Variable Names |
|
List of Variable Names |
|
List of Variable Names and Lengths |
|
List of Variable Names and Types |
|
List-Style Specification of Housekeeping Genes |
|
List-Style Specification of Individual Variables |
|
List-Style Specification of Intensity Variables to Bin |
|
List-Style Specification of Marker Variables |
|
List-Style Specification of Trait Variables |
|
List-Style Specification of Variables to be Included for Normalization |
|
LOH Columns to Include |
|
LOH Measurements to Include (100K or 500K Arrays) |
|
Map Data Set |
|
Map File |
|
MAP Files |
|
Marker Data Set |
|
Marker ID Variable |
|
Marker Label |
|
Marker Name Variable |
|
Marker Type |
|
Marker Variables |
|
Master Variations (masterVarBeta) |
|
Matrix File to Import |
|
Maximum Column Length |
|
Maximum Intron Bin Size |
|
Measures to Include (Chromosomes Data) |
|
Measures to Include (CopyNumber Data) |
|
Measures to Include (SNP6 Array) |
|
Merge Variables |
|
Meta Probeset File |
|
MiniML-formatted File |
|
Minimum Number of Columns to Scan |
|
Minimum Number of Probes to Summarize Probe-Set Level |
|
Missing Covariate Value |
|
Missing Genotype Value |
|
Missing Individuals Threshold |
|
Missing Phenotype Value |
|
Missing Quantitative Trait Value |
|
Name of Phenotype Variable |
|
Names of Variables Preceding Genotype Probability Columns |
|
NBeads Output Data Set |
|
Negative Control Method |
|
New Study |
|
New Variable Names for Experimental Design |
|
No Family ID Column |
|
No Parent ID Columns |
|
No Phenotype Column |
|
No Sex Column |
|
Normalization |
|
Normalize copy number data using autosomes |
|
Normalize SNP data using autosomes |
|
Number of CEL Files to Process at a Time |
|
Number of Channels in Each File |
|
Number of Data Files to Process at a Time |
|
Number of Genotype Probability Columns |
|
Number of Genotype Probability Columns per Individual |
|
Number of Rows in Each Bin |
|
Number of Rows to Scan |
|
Options |
|
Order Annotation Data Set by SNP column order |
|
Output Allele Intensity Data Set |
|
Output Allele Intensity Experimental Design Data Set |
|
Output Annotation Data Set |
|
Output Copy Number Intensity Data Set |
|
Output Data Set |
|
Output Data Set Name |
|
Output Data Set of Normalization Factors |
|
Output Data Set of Selected Stable Genes |
|
Output Expected Genotype Data Set |
|
Output Experimental Design Data Set |
|
Output File Name |
|
Output File Prefix |
|
Output Folder |
|
Output Genotype by Chromosomes |
|
Output Genotype Data Set |
|
Output Genotype Probabilities Data Set |
|
Output Genotype Threshold Data Set |
|
Output Map Data Set |
|
Output Probe-level Intensity Data Set |
|
Output Sequence Data Set |
|
Output SNP-summarized Copy Number Intensity Data Set |
|
Output Wide Data Set |
|
p-Value Cutoff for Segregation Test |
|
Parent 1 ID Variable |
|
Parent 2 ID Variable |
|
Parse Associated Gene Column |
|
PDF or RTF Output File |
|
PDF Output File |
|
PDF Output File Name |
|
PED or FAM Files |
|
Pedigree File |
|
Percentage of Data to Be Included in Training Data |
|
Percentage of Samples Below Cut-off(s) for Dropping SNPs |
|
Percentage of samples for dropping SNPs |
|
Perform log2 transform |
|
Perform log2 transform after scaling |
|
Phenotype File has a Header Row |
|
Ploidy Level |
|
Ploidy Type |
|
PM Correction |
|
Position |
|
Position Variable |
|
Positive Control Limit of Detection QC |
|
Positive Control Linearity QC |
|
Positive Control Method |
|
Prefix for New Columns |
|
Prefix for Output Data Set Names |
|
Prefix for Output Experimental Design Data Set Names |
|
Prefix for SNP Names |
|
Prefix to Append to SNP Column Names |
|
Prefix to Append to SNP Column Names (for Full Data Table) |
|
Prefixes of SNPs to Include in Data Sets |
|
Probe Coordinates Output Data Set |
|
Probe Group File |
|
Probe Normalization |
|
Probe Normalization Method |
|
Probeset File |
|
Probeset Variable |
|
Probe Variable |
|
QC Control File |
|
QC Output Data Set |
|
QC Probe Output Data Set |
|
Quality Flag Output Data Set |
|
Quantitative Variables |
|
Reference File |
|
Reference Gene Normalization |
|
Reference Genes to Use |
|
Reference Genome File |
|
Remove AFFX Control SNPs from output data set(s) |
|
Remove Control Genes |
|
Remove PCR duplicates |
|
Remove Reference Genes in Output |
|
Row Number of Variable Names |
|
Sample File |
|
Sample File |
|
Sample Files |
|
Sample Variable |
|
SAS Code for Customized Flagging Rule |
|
SAS Code to Create Columns |
|
SAS Code to Create New Design Variables |
|
Save as SAS Data Set |
|
Scaling Factor |
|
SD Output Data Set |
|
Segments CN Data Set |
|
Segments CNNeutralLOH Data Set |
|
Segments LOH Data Set |
|
Segments Mosaicism Data Set |
|
Segments NormalDiploid Data Set |
|
Select an array |
|
Select Column to Parse |
|
Select Files |
|
Select key variable to merge files |
|
Select the folder containing .ARR files |
|
Select the folder containing pairs of ARR and data files |
|
Select the type of file(s) to input |
|
Selected Column |
|
Server Output Directory |
|
Set flagged data to missing |
|
Set heterozygous to missing |
|
Set individual genotypes to missing that are below: |
|
Shifting Factor |
|
Smoothing Bandwidth Multiplier |
|
SNP Annotation Data Set |
|
SNP Annotation SAS Data Set |
|
SNP Map File |
|
Sort genotype columns and map rows |
|
Source of Files |
|
Specify the maximum number of missing genotypes for a locus to be included in the output data set |
|
Specify your Input File |
|
Spot Coordinates Output Data Set |
|
Start |
|
Strand |
|
Study |
|
Summarization Method |
|
Summary Level |
|
Summary Method |
|
Tab-Formatted Probe Sequence File |
|
Track Gene Text Setting File |
|
Trait Variables |
|
Transformation Method |
|
Type of Array |
|
Type of File |
|
Type of File(s) |
|
Type of File Conversion |
|
Type of Map Files |
|
Type of Other Files |
|
Type of PED/FAM and Other Files |
|
Type of Phenotype Variable |
|
Unit for Genetic Distance |
|
Value of Chromosome Variable Indicating Non-autosomes |
|
Value of Columns Above to Be Associated with Non-autosomes |
|
Variables By Which to Merge Annotation Data |
|
Variables Containing Primary Data |
|
Variables to be Included for Normalization |
|
Variables to Keep in Output Data Set |
|
Variations (var) |
|
Variations at Known db SNP Loci (dbSNPAnnotated) |
|
Weighted with Kernel Density |
|
What kind of data files do you have? |
|
What type of Experiment is this? |
|
Width of Positional Bin |
|
Accession Number Variable |
|
Add Fold Change Filter to Select Significant Tests |
|
Add Marker Genes to Explore |
|
Add Mean Difference Filter to select significant tests |
|
Additional Bandwidth on Each Side of Tracks |
|
Additional Fixed Effects |
|
Additional Random Effects |
|
Adjustment Effects |
|
Allele Characters for A (P1 line) and B (P2 line) |
|
Alpha |
|
Alpha value for Beta distribution |
|
Analyze rare variants only |
|
Annotation Analysis Group Variable to Use |
|
Annotation Analysis Group Variable |
|
Annotation Analysis Group Variable for Collapsing Rare Variants |
|
Annotation Analysis Group (Gene e.g.) Variable |
|
Annotation Chromosome Variable |
|
Annotation Group Variable |
|
Annotation Input SAS Data Set |
|
Annotation Label Variable |
|
Annotation Location Variable |
|
Annotation Merge Variables |
|
Annotation Plotting Group Variable |
|
Annotation Position Variable |
|
Annotation SAS Data Set |
|
Apply a Shifted log2 Transformation for QC Analysis |
|
Association Tests |
|
Automated Linkage Group Clustering Method |
|
Bandwidth |
|
Beta value for Beta distribution |
|
Binary Trait Variable |
|
Binary Trait Variables |
|
Break linkage groups based on: |
|
Break linkage groups between markers with large ordered distances |
|
By Variables |
|
Calculate trend odds ratios |
|
Categorical Variables |
|
Categorical Variables Defining Groups |
|
Categorical Variables for Model |
|
Cells with Maximum Features Detected |
|
Cells with Minimum Features Detected |
|
Censor Values |
|
Censor Variable |
|
Center columns |
|
Center rows |
|
Change Output Folder to Workflow Folder in settings moved to right panel |
|
Chromosome Variable |
|
Cluster Significant Results |
|
Clustering Method |
|
Collapse rare variants within analysis group |
|
Color Theme |
|
Color Variable |
|
Color Variable Type |
|
Color Variables |
|
Compress the K matrix |
|
Compression Rate |
|
Compute Q Variables from PCA |
|
Compute results for annotated rows only |
|
Compute results for exon annotated rows only |
|
Compute sandwich (empirical) estimator of covariance matrix |
|
Control Levels for Difference Comparisons |
|
Control Levels for Differential Expression Comparisons |
|
Conversion for P-Values |
|
Correlation and Grouped Scatterplots |
|
Correlation and Principal Variance Components Analysis |
|
Create add-in package |
|
Cross Type |
|
Cumulative Proportion of Variation to Explain with Principal Components |
|
Current Study |
|
Data Set of Differences to Include from Comparison Set |
|
Define linkage groups based on the: |
|
Delete rows: |
|
Delete rows with Interquartile Range satisfying this expression |
|
Delete rows with Mean satisfying this expression |
|
Delete rows with Median satisfying this expression |
|
Delete rows with Number of Missing Values satisfying this expression |
|
Delete rows with Percentile satisfying this expression |
|
Delete rows with Standard Deviation satisfying this expression |
|
Denominator Degrees of Freedom Method |
|
Direction of the Cutoff |
|
Direction of the Fold Change Cutoff |
|
Direction of the Mean Difference Cutoff |
|
Display marker genotype cell color plots |
|
Display principal components plots |
|
Distribution Analysis |
|
Estimate LSMeans for these Fixed Effects |
|
Event Trait Value |
|
Exon (Probeset) ID Variable |
|
Exon Annotation Chromosome Variable |
|
Exon Annotation Label Variable |
|
Exon Annotation Merge Variables |
|
Exon Annotation Position Variable |
|
Exon Annotation SAS Data Set |
|
Exon Annotation Transcript Variable |
|
Expected Segregation Ratios for AA AB BB |
|
Experimental Design SAS Data Set |
|
Features Detected in Minimum Cells |
|
File Containing Estimate Statements |
|
Filter Data with Zero or Missing Values |
|
Filter Rows Whose Proportion of Zero/Missing Values Exceeds this Cutoff |
|
Filter to Include Data in Analysis |
|
Filter to Include Exon Annotation Rows for ANOVA |
|
Filter to Include Individuals |
|
Filter to Include Markers |
|
Filter to Include miRNA Annotation Rows |
|
Filter to Include Observations |
|
Filter to Include Transcript Annotation Rows for ANOVA |
|
Filter to Select Markers for Computing the K Matrix |
|
Filter to Select Markers for PCA |
|
Fix covariance parameters |
|
Fixed Effects for Differential Expression |
|
Fixed Effect Interactions with Exon ID Variable (Alternative Splicing) |
|
Fold Change Filter Cutoff |
|
Folder of Available Processes |
|
Folder of Available Settings |
|
Folder of Track Settings Files |
|
Format of Marker Variables |
|
Framework Linkage Group Variable |
|
Framework Map Data Set |
|
Framework Marker Name Variable |
|
Framework Order Variable |
|
GenBank Accession Variable |
|
Gene Description Variable |
|
Gene ID Variable |
|
Gene Length Variable |
|
Gene Symbol Variable |
|
Genes of Interest |
|
Genetic Distance Break Value |
|
Genotype Delimiter |
|
Genotyping Generation (n) |
|
Group Percentage for Deletion |
|
Grouping Method |
|
Grouping Recombination Fraction Threshold |
|
Hierarchical Clustering |
|
Hotelling’s T-squared Test |
|
ID Variables |
|
Include 3D plots |
|
Include adjusted p-values in addition to -log10(p-values) |
|
Include Fold Changes in Addition to log Fold Changes |
|
Include fold changes in addition to log2 fold changes |
|
Include p-values in addition to -log10(p-values) |
|
Individuals Minimum Proportion of Nonmissing Genotypes |
|
Input data is log-transformed |
|
Input Genotype SAS Data Set |
|
Input SAS Data Set |
|
Intensity Columns to Filter |
|
Interaction Effects |
|
JMP Journal Output File |
|
K-Means Clustering |
|
Kernel Function |
|
Label Variable |
|
Launch ANOVA for Differential Expression Analysis |
|
Launch ANOVA Interface |
|
List every model fit |
|
List-Style Specification of Intensity Columns to Filter |
|
List-Style Specification of Marker Variables |
|
List-Style Specification of Trait Variables |
|
List-Style Specification of Variables Whose Rows are to be Clustered |
|
-log10(p-value) Cutoff |
|
MAF Threshold for Rare Variants |
|
Map Function |
|
Marker Name Variable |
|
Marker Variables |
|
Max Iteration of t-SNE |
|
Maximum Dimension of K Matrix |
|
Maximum Dispersion to Filter Genes |
|
Maximum Mean to Filter Genes |
|
Maximum Number of Chromosomes Per Row in 3D Display |
|
Maximum Number of Clusters for K-Means |
|
Maximum Number of Principal Components |
|
Maximum Number of Principal Components to Model |
|
Mean Difference Filter Cutoff |
|
Method |
|
Minimum Dimension of K Matrix |
|
Minimum Dispersion to Filter Genes |
|
Minimum Distance of UMAP |
|
Minimum Mean to Filter Genes |
|
Minimum Number of Clusters for K-Means |
|
Minimum Number of Observations Required for a Branch |
|
Minimum Proportion of Nonmissing Genotypes |
|
Minimum X Chromosome Heterozygosity for Females |
|
Minor allele frequency at Marker Locus |
|
Minor Allele Frequency Threshold |
|
Minor Allele Frequency Threshold for Including SNPs |
|
miRNA ID Variable |
|
Model Data As: |
|
Model interactions of these Fixed Effects with the Exon ID Variable (Screen for possible alternative splicing) |
|
Modeling Distribution |
|
Multiple-Locus Regression Model |
|
Multiple-Locus Radial Basis Machine (Kernel Method) |
|
Multiple Testing Correction |
|
Multiple Testing Method |
|
Multiple Testing Method for Segregation Tests |
|
Normalization Method |
|
Number of Clusters |
|
Number of Clusters Expected |
|
Number of Epochs of UMAP |
|
Number of Linkage Groups |
|
Number of Markers in Each Group |
|
Number of Neighbors of UMAP |
|
Number of Principal Components |
|
Number of Principal Components to Use |
|
Number of Rows in Input Data for Testing Run |
|
Number of SNPs to Test |
|
Number of the First Principal Component to Model |
|
Number of Variable Genes to Keep |
|
Organism |
|
Output Data Set |
|
Output Data Set Containing Filtered Data |
|
Output Dimension of Embedding |
|
Output File Prefix |
|
Output Folder |
|
Output genotype LS means and diffs |
|
Output residuals from every model |
|
P-Value Adjustment |
|
p-Value Cutoff for Plots |
|
p-Value Cutoff for Segregation Test Plots |
|
PARMS Statement Values and/or Options |
|
PC Regression Model |
|
Pedigree ID |
|
Percentage of Mitochondria Genes Allowed |
|
Percentile to Compute for PCTL Statistic |
|
Perform Case-Control Association Tests |
|
Perform Missing Genotype by Trait Analysis |
|
Perform multiallelic analysis on multiallelic markers |
|
Perform shifted log2 transformation: |
|
Perplexity of t-SNE |
|
Plot Markers with significant p-values only |
|
Position Variable |
|
Prefix of Marker Variables |
|
Principal Component Analysis |
|
Principal Variance Component Effects for QC |
|
PROC GLIMMIX Estimation Method |
|
Random Effects |
|
Random Mating Generation (t) Prior to Inbreeding |
|
Random Statement Options |
|
Recode genotypes numerically (2,1,0) |
|
Recombination Fraction Break Value |
|
Recombination Fraction Cutoff |
|
Reference Trait Value |
|
Remove Mitochondrial Genes from Analysis |
|
Remove Ribosomal Genes from Analysis |
|
Replace Cluster Means with representative observations |
|
Replace highest values |
|
Replace intensities falling above this column percentile |
|
Replace intensities falling above this value |
|
Replace intensities falling at least this many standard deviations above the column mean |
|
Replace intensities falling at least this many standard deviations below the column mean |
|
Replace intensities falling below this column percentile |
|
Replace intensities falling below this value |
|
Replace lowest values |
|
Report SNP x Interaction Effect tests only |
|
Results to Include in the Review |
|
Review Output File |
|
Run Analyses Above... |
|
Run QC analyses: |
|
Run Subset and Reorder Genetic Data process to order marker data for QTL analysis |
|
Run t-SNE and UMAP (Appropriate R Packages Required) |
|
Scale columns |
|
Scale rows |
|
Select Comparison Set for Differential Expression Tests |
|
Select Comparison Set for Mean Differences Tests |
|
Select Method |
|
Separate and journal results by chromosome |
|
Sequence Kernel Association Test (SKAT) |
|
Server Output Directory |
|
Shifted log2 Transformation for ANOVA |
|
Shifted log2 Transformation for QC |
|
Shifting Factor |
|
Shifting Factor of log2 Transform for QC |
|
Shifting Factor of log2 Transform before Normalization or ANOVA |
|
Show Only: |
|
Single-Locus Genotype Tests Pearson chi-square and Fisher’s exact |
|
Single-Locus Regression Model |
|
SNP ID Variable |
|
SNPs: Minimum HWE p-Value |
|
SNPs Minimum Minor Allele Frequency |
|
SNPs Minimum Missing Genotype by Trait p-Value |
|
SNPs Minimum Proportion of Nonmissing Genotypes |
|
Sort settings by: |
|
Strata Variables |
|
Study |
|
Study Name |
|
Study Output Folder |
|
Tau Value for TPM |
|
Template Study |
|
Template Study Output Folder |
|
Terminate further processes when an error occurs |
|
Test on a subset of SNPs |
|
Track Settings Files |
|
Trait Value of Individuals to Include in HWE Test |
|
Trait Variables |
|
Transcript Annotation Chromosome Variable |
|
Transcript Annotation Label Variable |
|
Transcript Annotation Merge Variables |
|
Transcript Annotation Position Variable |
|
Transcript Annotation SAS Data Set |
|
Transcript Annotation Variables to Keep |
|
Transcript Cluster ID Variable |
|
Two Way Clustering |
|
Type of Trait |
|
Use lower boundary constraint of 0 for K matrix covariance parameter |
|
Use QTL data numeric coding from JMP Genomics versions prior to 5.1 |
|
Value Ordering for Nominal Color Variable |
|
Value to Use to Replace Highest Values |
|
Value to Use to Replace Lowest Values |
|
Variable Containing Names of Marker Variables |
|
Variable Gene Selection Method |
|
Variables By Which to Merge Exon Annotation Data |
|
Variables By Which to Merge Tx Annotation Data |
|
Variables Defining Blocks |
|
Variables Defining Groups |
|
Variables for QC Plotting Groups |
|
Variables to Keep in Linkage Map Data Set |
|
Variables to Keep in Output |
|
Variables to Retain in Linkage Map Data Set |
|
Variables Whose Rows are to be Clustered |
|
Variance Component Effects |
|
Variant Weights |
|
Where Clause for Subsetting Input Data Set in Test Run |
|
Width of Positional Group |
|
Workflow Folder |
|
Workflow Output Name |
|
Workflow to Journal |
|
Workflow to Run |
|
1-D Test Step in cM (1-D Genomewide Scan) |
|
2-D Test Step in cM (2-D Genomewide Scan) |
|
Absolute Mean Difference Cutoff for Continuous Predictors |
|
Absolute Proportion Difference Cutoff for Class Predictors |
|
Accession Number Variable |
|
Add markers dropped out from marker reduction analysis back to the linkage groups |
|
Additional Covariates |
|
Additional Fixed Effects |
|
Additional PROC CLUSTER Options |
|
Additional PROC TREE Options |
|
Additional Random Effects |
|
Adjust permutation p-values for multiple testing |
|
Affected Offspring Variables |
|
Affected Sib-Pair Tests |
|
Affected Value of Trait Variable |
|
Algorithm |
|
All markers are biallelic |
|
Allele Characters for A (P1 line) and B (P2 line) |
|
Allele Variables |
|
Alpha |
|
Alpha for Dprime Confidence Limits |
|
Alpha for LSMeans Confidence Intervals |
|
Alpha for Selecting PCs |
|
Alpha Level for Covariates |
|
Alpha Level for Empirical LOD Thresholds |
|
Alpha value for Beta distribution |
|
Annotation Accession Variable |
|
Annotation Analysis Group Variable |
|
Annotation Analysis Group Variable for Collapsing Rare Variants |
|
Annotation By Group Variable |
|
Annotation Group Variable |
|
Annotation Input SAS Data Set |
|
Annotation Label Variable |
|
Annotation Location Variable |
|
Annotation MAF Variable |
|
Annotation Major Allele Variable |
|
Annotation Minor Allele Variable |
|
Annotation Plotting Group Variable |
|
Annotation SAS Data Set |
|
Annotation Variables to Drop |
|
Annotation Variables to Keep |
|
Annotation Weight Variable |
|
Append markers dropped out from marker reduction analysis to the output data sets |
|
Append prefix to current marker name |
|
Apply adaptive weights |
|
Apply mean-correction to covariates |
|
Apply stopping rules for map order optimization |
|
Apply VIF for genomic control |
|
Association Tests |
|
Assume Hardy-Weinberg equilibrium at all loci |
|
Asymmetric Loss Fitting Proportion |
|
Automated Linkage Group Clustering Method |
|
Average Pool Size |
|
Backcross Parental Lines Variable |
|
Bandwidth |
|
Base Input SAS Data Set |
|
Beta value for Beta distribution |
|
Binary Trait Variable |
|
Binary Trait Variables |
|
Block Partition Variable |
|
Bootstrap Confidence Interval Alpha |
|
Bootstrap Samples |
|
Break linkage groups based on: |
|
Break linkage groups between markers with large ordered distances |
|
Build a Combined Wide Data Set |
|
By Variables |
|
Calculate allele odds ratios |
|
Calculate trend odds ratios |
|
Calculate p-values for F statistics |
|
Categorical Covariates |
|
Categorical Variables |
|
Category Variable |
|
Censor Limit (-log10 scale) |
|
Censor Limit |
|
Censor Values |
|
Censor Variable |
|
Censor Variables |
|
Choose a linkage grouping method |
|
Choose a method for RIL simulation |
|
Choose the first-generation mating type |
|
Choose the mating type |
|
Choose the multi-generation mating type |
|
Choose the selection direction |
|
Choose the selection direction for the index |
|
Choose the selection direction for the similarity |
|
Choose the selection direction for the trait |
|
Chromosome |
|
Chromosome Label |
|
Chromosome Label from Base Input SAS Data Set |
|
Chromosome Number |
|
Chromosome Variable |
|
Cluster Center Variable |
|
Cluster Variable |
|
Cluster Variables |
|
Clustering Method |
|
Cofactor Categorical Variables |
|
Cofactor Continuous Variables |
|
Color of Bars ({r,g,b}) |
|
Color Variable |
|
Color Variable Type |
|
Columns of Q Matrix sum to 1 |
|
Columns of Q Matrix sum to 1 in Q1 Model |
|
Columns of Q Matrix sum to 1 in Q2 Model |
|
Columns of Q Matrix sum to 1 in Q3 Model |
|
Compress output data set |
|
Compression Method |
|
Compression Rate |
|
Compute Cholesky Root of Matrix |
|
Compute sandwich (empirical) estimator of covariance matrix |
|
Compute selection index |
|
Compute the root of the matrix by SVD |
|
Constrain negative IBD estimates to 0 |
|
Continuous Covariates |
|
Continuous Trait Variables |
|
Control Marker Data Set - Sorted Marker List |
|
Control Marker Number |
|
Control Marker Selection Method |
|
Convergence Criterion |
|
Conversion for F Statistics p-Values |
|
Conversion for p-Values |
|
Correlation Radius for Clustering |
|
Correlation Value for Clustering |
|
Corresponding Key Chromosome Number Variable from Merge Input SAS Data Set (1-12) |
|
Corresponding Key Grid Variable from Merge Input SAS Data Set (1-12) |
|
Corresponding Key Marker Label from Merge Input SAS Data Set (1-12) |
|
Corresponding Key Testing Location Variable from Merge Input SAS Data Set (1-12) |
|
Create cell plot |
|
Create data set containing haplotype frequency estimates |
|
Create data set of covariance parameter estimates for every model fit |
|
Create data set with numerically coded genotypes |
|
Create data sets of CorrCoeff2 in matrix format |
|
Create frequency charts |
|
Create haplotype frequency charts |
|
Create Hierarchical Cluster of SNPs |
|
Create HTML output |
|
Create merged PCA output data set |
|
Create output data set containing allelic transmissions |
|
Create Parallel Plot of SNPs |
|
Create PARMS statement from optimal model covariance parameter estimates |
|
Create Phase Assignment Data Set |
|
Create SAS data set containing htSNP indicator variable |
|
Create Significance Indicator Columns |
|
Create Stability Point Plot |
|
Create subset data set |
|
Create tagSNP subset indicator variable |
|
Criterion for Evaluating Sets of htSNPs |
|
Criterion for Optimal Compression Level |
|
Criterion for Stopping Model Selection |
|
Cross Type |
|
Cumulative Proportion of Variation to Explain with Principal Components |
|
Current Value(s) Denoting Missing Genotypes or Alleles |
|
Cutoff Level of Tree Axis |
|
CV Partitioning Method |
|
D’ between Marker and Disease Locus |
|
Data Step Statements |
|
Define linkage groups based on the: |
|
Delete Nonmatching Rows |
|
Delete Rows Not in Base Input SAS Data Set |
|
Denominator Degrees of Freedom Method |
|
Dependent Categorical Variable |
|
Dependent Class Variable |
|
Display cell plot of Mendelian errors |
|
Display column attributes |
|
Display marker genotype cell color plots |
|
Display markers |
|
Display principal components plots |
|
Display QTL location |
|
Distance to Include Downstream and Upstream of Gene |
|
Distance Unit |
|
Distance Unit for Defining Maximum Range of LD Blocks |
|
Dprime Lower Confidence Limit greater than: |
|
Dprime Upper Confidence Limit greater than: |
|
Dprime Upper Confidence Limit less than: |
|
Drop Alleles with frequency below: |
|
Drop Last Allele for Each Marker |
|
Effect Estimate or Direction Variable |
|
Effect Estimate or Direction Variable is the odds ratio |
|
EigenCore Multiple Testing Method |
|
Environment Variables |
|
Estimate Rho and K Rho |
|
Estimate the Number of Founding Populations |
|
Estimated Frequency Cutoff for Combining Rare Haplotypes |
|
Estimation Method |
|
Evaluate individuals in the Input SAS Data Set without making crosses |
|
Event Trait Value |
|
Exclude single-SNP genes |
|
Expanded Genotype Recoding |
|
Expected Segregation Ratios for AA AB BB |
|
Extreme Sampling Percentile |
|
Family Association Tests |
|
Family Test Options |
|
Feature Selection Criterion |
|
File Filter Expression |
|
Filter Defining First SNP in Interaction |
|
Filter Defining Second SNP in Interaction |
|
Filter to Include Annotation Rows |
|
Filter to Include Linkage Groups |
|
Filter to Include Markers |
|
Filter to Include Markers (applies to both data sets) |
|
Filter to Include Observations |
|
Filter to Include Observations for HWE Test |
|
Filter to Include Predictor Categorical Variables |
|
Filter to Include Predictor Continuous Variables |
|
Filter to Include Rows in Annotation SAS Data Set |
|
Filter to Include Windows |
|
Filter to Select Null SNPs |
|
Filter to Specify Recurrent Parental Lines |
|
Filter Variables |
|
First Column to Display |
|
First Row to Display |
|
Fit Square Root of Recombination Fractions in MDS Algorithm |
|
Fix covariance parameters |
|
Fixed Threshold |
|
Flip alleles for A/T or C/G SNPs with major/minor alleles reversed from reference |
|
Folder Containing Scoring Code Files |
|
Folder of Input SAS Data Sets |
|
Folder of Linkage Map Files |
|
Force all markers into linkage groups |
|
Format of Marker Variables |
|
Format of SNP Variables |
|
Framework Linkage Group Variable |
|
Framework Map Data Set |
|
Framework Marker Name Variable |
|
Framework Order Variable |
|
Frequency Cutoff |
|
Frequency Cutoff for Combining Haplotypes |
|
Frequency Initialization |
|
Frequency Variable |
|
Function of Covariates |
|
Function of Trait Variable |
|
Gene By Variables |
|
Gene Input SAS Data Set |
|
Gene Label |
|
Gene Start Variable |
|
Gene Stop Variable |
|
Genetic Distance Break Value |
|
Genetic Distance Unit for Results Plots |
|
Genotype Data Set |
|
Genotype Delimiter |
|
Genotype Probability Data Set |
|
Genotype Probability Variables |
|
Genotype Recoding |
|
Genotype to code as 2 for the Trend Test |
|
Genotype to code as 2 for the Trend Test ORs |
|
Genotype Variable |
|
Genotyping Generation (n) |
|
Grouping LOD Score Threshold |
|
Grouping LOD Threshold |
|
Grouping Method |
|
Grouping Recombination Fraction Threshold |
|
Grouping Variable |
|
Haplotype Estimation Method |
|
Haplotype Frequency Data Set |
|
Heat Map Color Theme |
|
High-risk Allele Frequency |
|
Hold L at starting value |
|
Hold M at starting value |
|
Hold-Out Method |
|
Hold-Out Size, Specify as: |
|
Hotelling’s T-squared Test |
|
IBD Data Set |
|
IBS sharing counted for: |
|
ID Variables |
|
Identity By Descent Threshold |
|
Identity By State Threshold |
|
Impute zeros for missing continuous predictor values |
|
Impute zeros for missing values |
|
Inbreeding Coefficient |
|
Include 3D plots |
|
Include direction of variant effect in test |
|
Include framework markers in the K-Means clustering analysis |
|
Include self crosses |
|
Increase R Software memory limit |
|
Increment |
|
Individual ID |
|
Individual ID Variable |
|
Individuals to Include in Matrix |
|
Initial Number of Linkage Groups |
|
Input data contains means of genotypes on each environment |
|
Input Linkage Map SAS Data Set |
|
Input SAS Data Set |
|
Input Genotype SAS Data Set |
|
Input K Matrix Data Set |
|
Interaction Block Variables |
|
Interaction Effects |
|
Interactive Clustering Method |
|
Interactive Linkage Group Clustering Method |
|
Italics Value |
|
Italics Variable |
|
JMP Script Output File Name |
|
K for K-Fold CV |
|
K for K-Fold or 1/K Hold-Out |
|
K Matrix is compressed |
|
K Matrix is compressed in K1 Model |
|
K Matrix is compressed in K2 Model |
|
K Matrix Square Root Variables |
|
K Matrix Square Root Variables in K1 Model |
|
K Matrix Square Root Variables in K2 Model |
|
K-Means Clustering Method |
|
Keep original marker variables |
|
Kernel Function |
|
Key Chromosome Number Variable from Base Input SAS Data Set |
|
Key Chromosome Variable from Base Input SAS Data Set |
|
Key Grid Variable from Base Input SAS Data Set |
|
Key Marker Label from Base Input SAS Data Set |
|
Key Testing Location Variable from Base Input SAS Data Set |
|
Kinship Matrix Diagonal |
|
Krho |
|
L for Leave-L-Out |
|
Label Variable |
|
Linear-Bilinear Model |
|
Linkage Group Hierarchical Clustering Method |
|
Linkage Group Variable |
|
Linkage Group Variable 1 |
|
Linkage Group Variable 2 |
|
Linkage Map Files |
|
Linkage Map Weight List |
|
Linkage Phase Data Set |
|
Linkage Phase of Adjacent Markers |
|
List every model fit |
|
List of number of simulated progenies |
|
List of optimization direction (one value per trait) |
|
List of percent cut off (one value per generation) |
|
List of selection index cutoff (one value per generation) |
|
List of selection similarity cut off (one value per generation) |
|
List of threshold direction (one value per trait) |
|
List of threshold values (one value per trait) |
|
List of weight values for the selection index |
|
List-Style Specification of K Matrix Square Root Variables |
|
List-Style Specification of K Matrix Square Root Variables in K1 Model |
|
List-Style Specification of K Matrix Square Root Variables in K2 Model |
|
List-Style Specification of LOD Score Variables |
|
List-Style Specification of Marker Variables |
|
List-Style Specification of Matrix Variables |
|
List-Style Specification of Numeric SNP Variables |
|
List-Style Specification of Predictor Categorical Variables |
|
List-Style Specification of Predictor Continuous Variables |
|
List-Style Specification of Q Matrix Variables |
|
List-Style Specification of Q Matrix Variables in Q1 Model |
|
List-Style Specification of Q Matrix Variables in Q2 Model |
|
List-Style Specification of Q Matrix Variables in Q3 Model |
|
List-Style Specification of Recombination Rate Variables |
|
List-Style Specification of SNP Variables |
|
List-Style Specification of SNP Variables to Keep in Output Data Set |
|
List-Style Specification of SNP Variables to Retain in Output Data Set |
|
List-Style Specification of Trait Variables |
|
List-Style Specification of Variables to Be Standardized |
|
List-Style Specification of Variables to Keep in Output Data Set |
|
List-Style Specification of Variables to Retain in Output Data Set |
|
Listing for Each Model Fit |
|
Location Variable |
|
LOD Score Break Value |
|
LOD Score ID Variable |
|
LOD Score SAS Data Set |
|
LOD Score Variables |
|
LOD Threshold [1,10] |
|
LOD Threshold for Entry into the MIM Model |
|
LOD Threshold for Staying in the MIM Model |
|
-log10(p-Value) Cutoff |
|
log10 Regularization Parameter |
|
MAF Threshold for Rare Variants |
|
Main Test Step in cM |
|
Major Allele Variable |
|
MANOVA Statistic |
|
Map Function |
|
Map 1 Label |
|
Map 2 Label |
|
Marker 1 Label |
|
Marker 2 Label |
|
Marker 1 Location |
|
Marker 2 Location |
|
Marker Genotype Variables |
|
Marker ID Variable |
|
Marker ID Merge Variable |
|
Marker Label |
|
Marker Location Unit |
|
Marker locus is disease locus |
|
Marker Name Variable |
|
Marker Name Variable 1 |
|
Marker Name Variable 2 |
|
Marker Names Variable |
|
Marker Order Variable |
|
Marker Physical Position |
|
Marker Position |
|
Marker Type |
|
Marker Variables |
|
Maternal Value of the Sex Variable |
|
Matrix Variables |
|
Max Number of Categories Allowed in a Predictor |
|
Max Number of Effects in the Model |
|
Max Number of Variables to Consider for Splitting a Node |
|
Maximum |
|
Maximum Convergency Tolerance |
|
Maximum Dimension of K Matrix |
|
Maximum Depth of Tree |
|
Maximum Distance |
|
Maximum Interval Window List |
|
Maximum Iterations |
|
Maximum Number of Chromosomes Per Row in 3D Display |
|
Maximum Number of Clusters |
|
Maximum Number of Filtered Predictors |
|
Maximum Number of Iterations |
|
Maximum Number of Intervals to Fit Together as a Region |
|
Maximum Number of K-Means Clusters / Predictors |
|
Maximum Number of Principal Components |
|
Maximum Number of Steps |
|
Maximum Number of Trees |
|
Maximum Number of Variables to Select with Model Averaging |
|
Maximum Number of Variables to Select with Pooling |
|
Maximum Order of Interactions |
|
Maximum Range of LD Blocks |
|
Maximum Recombination Fraction Threshold |
|
Maximum Subset Size |
|
Maximum Time per Algorithm Iteration (in minutes) |
|
Maximum X Chromosome Heterozygosity for Males |
|
Mean Square Blocks or Replicates within Environments |
|
Mean Square Environment |
|
Mean Square Error |
|
Mean Square Error Degrees of Freedom |
|
Measure for LD Contour Plot |
|
Measure for LD Decay Plot |
|
Measure of Genetic Distance |
|
Merge Individual ID Variable |
|
Merge Input SAS Data Set (1-12) |
|
Merge Key Variables |
|
Method to Order Populations |
|
Method to Use |
|
Minimum |
|
Minimum Dimension of K Matrix |
|
Minimum LOD Threshold |
|
Minimum Number of Linkage Groups |
|
Minimum Number of Observations Required for a Branch |
|
Minimum Number of Offspring Sharing for Computing Runs |
|
Minimum Proportion of Nonmissing Genotypes |
|
Minimum Run Length for Including in Output |
|
Minimum X Chromosome Heterozygosity for Females |
|
Minor Allele Frequency at Marker Locus |
|
Minor Allele Frequency Threshold |
|
Minor Allele Frequency Threshold for Including SNPs |
|
Model Selection Method |
|
Multi-Marker Model Selection |
|
Multiple-Locus Regression Model |
|
Multiple Testing Correction |
|
Multiple Testing Method |
|
Multiple Testing Method for Segregation Tests |
|
Nearby Marker Recombination Constraint |
|
Nominalize Continuous Dependent Variables |
|
Null SNP Variables |
|
Number of Backcross Generations |
|
Number of Clusters |
|
Number of Clusters for Automated Compression |
|
Number of Columns |
|
Number of Contours |
|
Number of Distinct Genotypes |
|
Number of Generations |
|
Nearby LOD Score Constraint |
|
Number of Founding Populations |
|
Number of Intervals to Overlap in Consecutive Regions |
|
Number of Legend Decimals |
|
Number of Legend Levels |
|
Number of Linkage Groups |
|
Number of Markers in Each Group |
|
Number of model averaging samples |
|
Number of Permutations |
|
Number of Permutations or Simulations to Perform |
|
Number of Permutations to Compute |
|
Number of Permutations to Perform |
|
Number of Principal Components |
|
Number of Random Hold-Out Iterations |
|
Number of Reconfigurations |
|
Number of Representative Markers |
|
Number of Rounds of Selection |
|
Number of Rows |
|
Number of Selections to Display |
|
Number of Selfing Generations |
|
Number of Shuffles |
|
Number of Simulated Progeny for Each Cross |
|
Number of Simulations for MAX Test |
|
Number of Starts |
|
Number of Steps |
|
Number of Variables to Process at a Time |
|
Numeric Marker Variables |
|
Numeric SNP Variables |
|
Numerical Parameter for Advanced Standardization Methods |
|
Observed Frequency Cutoff for Dropping Rare Haplotypes |
|
Optimize the continuous predictor set |
|
Optimized Automated Clustering Method |
|
Options to Define Cluster Membership |
|
Order Algorithm |
|
Order Data Set |
|
Other Accession Number Variables |
|
Other Chromosome Variables |
|
Other Effect Estimate Variables |
|
Other Location Variables |
|
Other Major Allele Variables |
|
Other p-Value Variables |
|
Other Sample Size Variables |
|
Other SNP ID Variables |
|
Other Standard Error Variables |
|
Other Variables to Keep in Output Data Set |
|
Other Variables to Retain in Output Data Set |
|
Output Annotation Data Set |
|
Output covariance parameter estimates from every model |
|
Output Data Set |
|
Output Data Set Prefix |
|
Output File Name |
|
Output File Prefix |
|
Output fitness statistics for every model |
|
Output Folder |
|
Output Genotype Data Set |
|
Output genotype LS means |
|
Output genotype LS means and diffs |
|
Output M and L Data Set |
|
Output Map Data Set |
|
Output markers with significant p-values only |
|
Output most probable haplotype pair only |
|
Output parameter estimates from every model |
|
Output predicted values from every model |
|
Output R-Square from the logistic regression of binary, nominal, and ordinal traits |
|
Output residuals from every model |
|
Output SAS data set of between and within family component variables for the O-QTDT |
|
Output simulated progenies data set |
|
Output survival function estimates for viewing survival curves |
|
P for P-Percent-Hold-Out |
|
p-Value Adjustment |
|
p-Value Combination Method |
|
p-Value Cutoff for Segregation Test Plots |
|
p-Value Variable |
|
Parent 1 ID |
|
Parent 2 ID |
|
Parent Variables |
|
PARMS Statement Values and/or Options |
|
PC Regression Model |
|
PCA Data Set |
|
Pedigree Data Set |
|
Pedigree ID |
|
Pedigree ID Variable |
|
Pedigree ID Variable in K1 Model |
|
Pedigree ID Variable in K2 Model |
|
Percent Cut Off |
|
Perform 2-sided Test |
|
Perform association tests on selected markers |
|
Perform association tests on unselected markers conditional on selected markers |
|
Perform EigenCorr to select PCs |
|
Perform F statistics calculations |
|
Perform genetic distance matrix calculations |
|
Perform LD calculations for all pairs within annotation groups |
|
Perform model averaging |
|
Perform poolwise selection |
|
Perform Principal Components Analysis |
|
Perform recoding with respect to the: |
|
Perform SAS-based clustering on the genetic distance matrix |
|
Permutations |
|
Phase Assignment ID Variables |
|
Phase Assignment Probability Cutoff |
|
Phased Haplotypes Data Set |
|
Phenotyping Generation (m) |
|
Ploidy Number |
|
Plot haplotypes with significant p-values only |
|
Plot heatmaps for linkage groups |
|
Plot Markers with significant p-values only |
|
Plot Markers with significant F ST p-values only |
|
Plot Relationship Matrix heat map |
|
Population Prevalence |
|
Population Variable |
|
Position Variable |
|
Position Variable 1 |
|
Position Variable 2 |
|
Power Values |
|
Predictor Categorical Variables |
|
Predictor Continuous Variables |
|
Prefix |
|
Prefix for Column Names of Expanded Genotypes |
|
Prefix for Column Names of Recoded Genotypes |
|
Prefix for Naming Distance Output Variables |
|
Prefix for Naming Output Variables |
|
Preliminary Delimiter Separating Annotation Categories (Enclose in Quotes) |
|
Prior Probabilities / Prevalences |
|
PROC GENESELECT Statement Options |
|
PROC GLIMMIX Estimation Method |
|
PROC MIXED Estimation Method |
|
Proportion of Alleles Identical by State Threshold |
|
Proportion of Informative Pairs in Strong LD greater than: |
|
Q and K Data Set |
|
Q Matrix Variables |
|
Q Matrix Variables in Q1 Model |
|
Q Matrix Variables in Q2 Model |
|
Q Matrix Variables in Q3 Model |
|
QTDT Tests |
|
QTL Effect Size Variables from Base Input SAS Data Set |
|
QTL Effect Size Variables from Merge Input SAS Data Set (1-12) |
|
QTL Indicator Variable from Base Input SAS Data Set |
|
QTL Indicator Variable from Merge Input SAS Data Set (1-12) |
|
QTL Mapping Method |
|
QTL Mapping Model Algorithm |
|
QTL Test Size Variables from Base Input SAS Data Set |
|
QTL Test Size Variables from Merge Input SAS Data Set (1-12) |
|
QTL Test Step in cM |
|
Quantile Level |
|
Quantitative Trait Variables |
|
Quantitative Variables |
|
R Software Memory Size (Mb) |
|
R-squared Threshold |
|
Radial Basis Machine (Kernel Method) |
|
Random Effects |
|
Random Mating Generation (t) Prior to Inbreeding |
|
Random Number Seed |
|
Random Number Seed for Forest |
|
Random Number Seed for Testing F Statistics |
|
Random Statement Options |
|
Range of Markers Variable |
|
Rare Variant Recoding |
|
RATE= Option |
|
Recombination Fraction Break Value |
|
Recombination Fraction Cutoff |
|
Proximity to Optimal Mapping Order |
|
Recombination Rate Variables |
|
Reference Annotation SAS Data Set |
|
Reference Annotation Label Variable |
|
Reference Annotation Major Allele Variable |
|
Reference Annotation Minor Allele Variable |
|
Reference Population for FST |
|
Reference Trait Value |
|
Relationship Matrix to Compute |
|
Risk of Observing the Trait in the Heterozygous Genotype (A/a) Relative to the Homozygous Recessive Genotype (a/a) |
|
Risk of Observing the Trait in the Homozygous Dominant Genotype (A/A) Relative to the Homozygous Recessive Genotype (a/a) |
|
Remove markers not found in Annotation SAS Data Set |
|
Reorder Variables |
|
Replicate Variable |
|
Report SNP x Interaction Effect tests only |
|
Reverse Color Theme |
|
Rho |
|
Sample Proportion of Cases |
|
Sample Size Variable |
|
Sample Sizes |
|
SAS Data Set Indicating Which Crosses to Simulate |
|
SAS Data Sets |
|
Save Data Set for Each Window |
|
Scoring Code Files |
|
Search Method |
|
Select best simulated progenies based on trait values |
|
Select simulated progenies based on similarity to parents |
|
Selection Criterion for Main Effect Search and Drop |
|
Selection Criterion for Interaction Search and Drop |
|
Selection Index Cut Off |
|
Sequence Kernel Association Test (SKAT) |
|
Server Output Directory |
|
Sex Variable |
|
Shuffle Markers |
|
Shuffling LOD Threshold |
|
Shuffling Window Size |
|
Significance Level for Entry into the MIM Model |
|
Significance Level for Entry into the Model |
|
Significance Level for Staying in the MIM Model |
|
Significance Level for Staying in the Model |
|
Similarity Measure |
|
Simulate data from all crosses |
|
Simulate multiple generations |
|
Simulate progenies |
|
Simulate RIL progenies |
|
SL for Adding Variables |
|
SL for Keeping Variables |
|
SL for Keeping Variables in the Selected Model |
|
Sliding Window Size |
|
Sliding Window Variable |
|
SNP Data Set |
|
SNP ID Variable |
|
SNP Variables |
|
SNP Variables (Coded Numerically) |
|
SNP Variables to Keep in Output Data Set |
|
SNP Variables to Retain in Output Data Set |
|
Specification of Regularization Parameter (Lambda) |
|
Standard Error Estimate |
|
Standard Error Variable |
|
Standardize genotypes |
|
Standardize Predictors Row-Wise |
|
Standardization Method for Predictor Continuous Variables |
|
Starting Value for E, the Exponential Decline of Rho with Physical Distance |
|
Starting Value for L, the Bias at Large Distance |
|
Starting Value for M, the Proportion of the Youngest Haplotype that is Monophyletic |
|
Statistical Testing Method for Continuous Predictors |
|
Stepwise EM Cutoff |
|
Strata Variable |
|
Strata Variables |
|
Study |
|
Subset Size |
|
Suppress all graphical and HTML output |
|
Tau Value for TPM |
|
Temperature |
|
Temperature Reduction Factor |
|
Test allelic association for LD |
|
Test Data Set |
|
Test each marker individually |
|
Test for HWE |
|
Test Individual Haplotypes |
|
Test Statistic |
|
Test Window Size in cM |
|
Tests |
|
Top Cross Tester Lines Indicator Variable |
|
TOTAL= Option |
|
Trait Variable |
|
Trait Variables |
|
Transformation of Input p-Values |
|
Transformation of Output p-Values |
|
Transformation for Predictor Continuous Variables |
|
Transpose data for cell plot |
|
Treat missing genotypes as: |
|
Type I Error Rate |
|
Type of Coefficients to Calculate |
|
Type of Kernel to Use |
|
Type of Model |
|
Type of Tests to Perform |
|
Type of Trait |
|
Type of Weight to Use |
|
Usage of K-Means Clusters |
|
Use a variable threshold for including variants |
|
Use Annotation Label Variable for Variable Prefixes |
|
Use Automated Hierarchical Clustering to Assign Linkage Groups |
|
Use bias corrected recombination formula for RIL |
|
Use dominant coding for trend test |
|
Use Forest to create interaction indicators |
|
Use Forest to filter predictors |
|
Use genetic map to simulate linkage |
|
Use grid computing |
|
Use K-Means clustering to reduce marker number |
|
Use K-Means clustering to reduce number of markers |
|
Use K-Means clustering to reduce predictors |
|
Use lower boundary constraint of 0 for K matrix covariance parameter |
|
Use Monte Carlo simulations for KBAC p-values |
|
Use QTL data numeric coding from JMP Genomics versions prior to 5.1 |
|
Use rank-based statistic for tests |
|
Use reported value of sex variable for genetic sex when ambiguous |
|
Use statistical testing to filter predictors |
|
Value of the Backcross Parental Lines Variable Indicating the Parental Line 1 |
|
Value of the Backcross Parental Lines Variable Indicating the Parental Line 2 |
|
Value Ordering for Nominal Color Variable |
|
Value Ordering for Nominal Variables |
|
Value Representing Cases |
|
Value to Impute for Missing Genotypes |
|
Variable By Which to Merge Annotation Data |
|
Variable Containing Names of Marker Variables |
|
Variable to Define Tree Axis |
|
Variables to Be Standardized |
|
Variables to Drop |
|
Variables to Keep in Linkage Map Data Set |
|
Variables to Keep in Output Data Set |
|
Variables to Keep in PCA Data Set |
|
Variables to Retain in Linkage Map Data Set |
|
Variables to Retain in Output Data Set |
|
Variant Weights |
|
Weight the MDS Fit Based on Recombination Fractions |
|
Weight Variable |
|
Weighting Method for Sibships |
|
Width of Positional Group |
|
Window Overlap |
|
Window Size in cM |
|
Window Size Unit |
|
X-linked Marker Clause |
|
X-linked Markers Clause |
|
X-linked Markers Clause |
|
Add Mean Difference filter to select significant tests |
|
Additional Bandwidth on Each Side of Tracks |
|
Adjustment Effects |
|
Alpha |
|
Annotation Chromosome Variable |
|
Annotation Label Variable |
|
Annotation Merge Variables |
|
Annotation Position Variable |
|
Annotation SAS Data Set |
|
Annotation Variables to Keep |
|
Annotation Variables to Keep in Output Data Set |
|
Annotation Variables to Retain in Output Data Set |
|
Bin Method |
|
Bin Summary Statistic |
|
By Variables |
|
Calculate the absolute value of the differences |
|
Categorical Variables |
|
Categorical Variables Defining Groups |
|
Center rows |
|
Chromosome Variable |
|
Cluster significant Mean profiles |
|
Cluster Significant Results |
|
Color Theme |
|
Color Variables |
|
Compute Pearson covariances instead of correlations |
|
Compute results for annotated rows only |
|
Control Levels |
|
Control Levels for Difference Comparisons |
|
Control Reference Value |
|
Control Set Summary Statistic |
|
Cumulative Proportion of Variation to Explain |
|
Data Set to Use for Filter |
|
Density Smoothing Bandwidth Computation Method |
|
Density Smoothing Bandwidth Multiplier |
|
Direction of the Cutoff |
|
Display detailed distribution statistics and histograms |
|
Display Format for Density Grid Points |
|
Display side-by-side box plots |
|
Display Standard Deviation versus Mean plots |
|
Exclude rows with missing physical position |
|
Experimental Design SAS Data Set |
|
Experimental Factor Variables |
|
File Containing Estimate Statements |
|
Filter to Include Annotation Rows |
|
Filter to Include Observations |
|
Filter to Include Rows |
|
Folder of Track Settings Files |
|
GenBank Accession Variable |
|
Gene Description Variable |
|
Gene Variable |
|
Gene Symbol Variable |
|
ID Variable |
|
ID Variables to Keep |
|
Include adjusted p-values in addition to -log10(p-values) |
|
Include p-values in addition to -log10(p-values) |
|
Include Standard Errors |
|
Include t-Statistics |
|
Input SAS Data Set |
|
Intensity Variables to Bin |
|
JMP Script Output file Name |
|
JMP Script Output File Name |
|
JSL Output File |
|
K for Circular B S Minor Arc |
|
Key Variable(s) to Merge with Input SAS Data Set |
|
Label Variable |
|
List every model fit |
|
List-Style Specification of Intensity Variables to Bin |
|
List-Style Specification of Variables |
|
List-Style Specification of Variables for Which to Display Distributions |
|
List-Style Specification of Variables to be Standardized |
|
List-Style Specification of Variables to Partition Intensity Values |
|
List-Style Specification of With Variables |
|
-log(Alpha) for Stopping Rule |
|
-log10(p-value) Cutoff |
|
Maximum Depth of Recursion |
|
Maximum Number of Principal Components to Apply |
|
Mean Difference Filter Cutoff |
|
Merge Annotation into Residuals Data Set |
|
Merge Key Variables to Associate with Input SAS Data Set |
|
Minimum Segment Size |
|
Multiple Testing Method |
|
Negative Mean Intensity Maximum [<=0] |
|
Number of Density Grid Points |
|
Number of Markers in Each Bin |
|
Number of Permutations |
|
Number of the First Principal Component for VCA |
|
Numerical Parameter for Advanced Standardization Methods |
|
Organism |
|
Output Data Set |
|
Output Eigenvalues Data Set |
|
Output Experimental Design Data Set |
|
Output Folder |
|
Output experimental samples only |
|
Output Prefix |
|
Output Statistics Data Set |
|
Output Test Data Set |
|
Output Variance Components Data Set |
|
Overlay density estimates |
|
Perform log2 transform after standardization |
|
Perform LOH targeted subtraction |
|
Plot standardized residuals |
|
Position Variable |
|
Positive Mean Intensity Minimum [>=0] |
|
Probe or SNP ID Variable |
|
PROC GENESELECT Statement Options |
|
Sample Set(s) to Use for Subtraction |
|
Scale rows |
|
Select Comparison Set for Mean Differences Tests |
|
Separate and journal results by chromosome |
|
Server Output Directory |
|
Shifting Factor |
|
Shrink variances using Empirical Bayes |
|
SNP ID Variable |
|
Standardization Method |
|
Standardization Method for Comparing Means |
|
Standardization Statistics Input SAS Data Set |
|
Standardize |
|
Standardized Residuals Output Data Set Name |
|
Study |
|
Subset Data Set to Use for Normalization |
|
Track Settings Files |
|
Type of Correlation |
|
Uniformly scale histograms in detail plots |
|
Uniformly scale y-axes in Volcano and Chromosome Position plots |
|
Uniformly scale y-axes in Volcano plots |
|
Variable Distinguishing Bivariate Observations |
|
Variables |
|
Variables By Which to Merge Annotation Data |
|
Variables By Which to Merge Filter Data Set |
|
Variables Defining Analysis Groups |
|
Variables Defining Blocks |
|
Variables Defining Control Sets |
|
Variables Defining Groups for Mean Processing |
|
Variables for Which to Display Distributions |
|
Variables to Keep in Output |
|
Variables to be Standardized |
|
Variables to Partition Intensity Values |
|
Variance Component Effects |
|
Width of Positional Bin |
|
With Variables |
|
Alpha |
|
Bandwidth |
|
Between-Group Overlay Jitter |
|
Bin Method |
|
Bin Size |
|
Bin Summary Statistic |
|
Bin Width |
|
By Variable |
|
By Variables |
|
Filter to Include Observations |
|
ID Variables to Keep |
|
Input SAS Data Set |
|
JMP Script Output file Name |
|
JMP Script Output File Name |
|
Label Variable |
|
List-Style Specification of y Variables |
|
List-Style Specification of y Variables Group A |
|
List-Style Specification of y Variables Group B |
|
List-Style Specification of y Variables to Bin |
|
List-Style Specification of y Variables to Detrend |
|
log2 transform areas or heights |
|
Lower and Upper x-Axis Values for Noise Intervals |
|
Maximum Number of Peaks to Compute |
|
Noise Baseline Fitting Option |
|
Noise Cutoff |
|
Output Data Set |
|
Output Details Data Set |
|
Output Folder |
|
Peak Cutoff |
|
Peak Quantity to Output |
|
Percentage of Maximum Signal Below Which is Noise |
|
Plot raw data |
|
Response Density SAS Statements |
|
Scale the area under the curve |
|
Server Output Directory |
|
Statistical Test |
|
Study |
|
Trim below zero |
|
Trim Peak Maximum |
|
Trim Valley Minimum |
|
Within-Group Overlay Jitter |
|
x Smoothing Bandwidth Multiplier |
|
x Variable |
|
x Variable Lower Bound |
|
x Variable Number of Grid Points |
|
x Variable Upper Bound |
|
y Smoothing Bandwidth Multiplier |
|
y Variable |
|
y Variable Lower Bound |
|
y Variable Number of Grid Points |
|
y Variable Upper Bound |
|
y Variables |
|
y Variables to Bin |
|
y Variables to Detrend |
|
y Variables Group A |
|
y Variables Group B |
|
z Variable |
|
z Variable Lower Bound |
|
z Variable Upper Bound |
|
z Variables |
|
Accumulative Proportion of Variation |
|
Add Mean Difference filter to select significant tests |
|
Additional Bandwidth on Each Side of Tracks |
|
Additional Covariates |
|
Additional Fixed Effects |
|
Additional PROC MIXED Statements |
|
Adjust Counts by Total Counts |
|
Adjustment Effects |
|
Allele Variable |
|
Alpha |
|
Alpha Values |
|
Annotation Chromosome Variable |
|
Annotation Label Variable |
|
Annotation Merge Variables |
|
Annotation Merging Variable |
|
Annotation Position Variable |
|
Annotation SAS Data Set |
|
Annotation Title Variables |
|
Annotation Variables to Keep |
|
Apply Certain Samples as Reference |
|
Apply data from autosomes for normalization |
|
Apply kernel density estimation for MA plot |
|
Apply normalized data for MA plot |
|
Apply reference baseline from previously input data set |
|
Array Standardization Method |
|
Apply weighting approach for trimmed mean |
|
Array Variables to Plot |
|
Bandwidth Multiplier of x-Dimension |
|
Bandwidth Multiplier of y-Dimension |
|
Baseline |
|
Baseline in Reference SAS Data Set |
|
Baseline Quantification |
|
Baseline reference data is log-transformed |
|
Baseline Reference SAS Data Set |
|
Baseline Value |
|
Baseline Variable |
|
Batch Profile Input SAS Data Set |
|
Biomaterial Provider |
|
Block Variable |
|
By Variable |
|
By Variables |
|
By Variables for Loess Normalization |
|
Calculate the absolute value of the differences |
|
Catalog Number |
|
Categorical Variables |
|
Categorical Variables Defining Groups |
|
Cells with Maximum Features Detected |
|
Cells with Minimum Features Detected |
|
Censor Variable |
|
Center rows |
|
Characteristics |
|
Chromosome Variable |
|
Cluster significant Mean profiles |
|
Cluster Significant Results |
|
Coating |
|
Color Scale |
|
Color Variable |
|
Color Variables |
|
Column to Identify Control Rows in the EDDS |
|
Columns by Which to Merge with Input SAS Data Set |
|
Columns Defining Batches |
|
Component Output Data Set Name |
|
Compute Component Fixed-Effect Tests |
|
Compute Multiple Testing Adjustment Separately for Each Test |
|
Compute Pearson covariances instead of correlations |
|
Compute results for annotated rows only |
|
Compute results for secondary annotated rows only |
|
Constants for Each Variance Component |
|
Contributors |
|
Constant to Apply |
|
Control Levels |
|
Control Set Design |
|
Control Levels for Difference Comparisons |
|
Control Levels for Differential Expression Comparisons |
|
Control Set Summary Statistic |
|
Coordinate Data Set |
|
Coordinate Merge Variables |
|
Covariates for Differential Expression |
|
Create JMP Surface plot |
|
Cumulative Proportion of Variation to Explain |
|
Data Processing |
|
Data Set of Differences to Include from Comparison Set |
|
Data Set to Use for Filter |
|
Delete nonmatching rows |
|
Delete rows |
|
Delete rows not in First Tall Data Set |
|
Delete rows with at least this percentage of Missing values |
|
Delete rows with Interquartile Range satisfying this expression (use keyword IQR) |
|
Delete rows with Mean satisfying this expression (use keyword MEAN) |
|
Delete rows with Median satisfying this expression (use keyword MEDIAN) |
|
Delete Rows with number of missing values satisfying this expression (use keyword NMISS) |
|
Delete rows with Percentile satisfying this expression (use keyword PCTL) |
|
Delete rows with Standard Deviation satisfying this expression (use keyword STD) |
|
Density Smoothing Bandwidth Computation Method |
|
Density Smoothing Bandwidth Multiplier |
|
Description |
|
Design-Level By Variables |
|
Design-Level Grouping Variables |
|
Differential Expression Effects to Keep in the Normalized Data |
|
Direction of the Cutoff |
|
Display Cumulative Percentage of Summary plots |
|
Display detailed distribution statistics and histograms |
|
Display Format for Density Grid Points |
|
Display side-by-side box plots |
|
Display Scatterplot matrices |
|
Display Standard Deviation versus Mean plots |
|
Distribution |
|
Model Distribution |
|
DNA data is log-transformed |
|
DNA Design Variables to be Added in Output Data Sets |
|
DNA Intensity Input SAS Data Set |
|
DNA Matching Variables |
|
Effect Sizes |
|
Experimental Design SAS Data Set |
|
Experimental Design Data Set Corresponding to Baseline Reference Data Set |
|
Experimental Design SAS Data Set of DNA Intensity |
|
Experimental Design SAS Data Set of RNA Intensity |
|
Experimental Factor Variables |
|
Exponential Multiplier of Kernel Density |
|
Extract Protocol |
|
Feature Variable |
|
Features Detected in Minimum Cells |
|
Fifth Experimental Design Data Set |
|
Fifth Tall Data Set |
|
File Containing Estimate Statements |
|
Filter data with Zero or Missing values |
|
Filter Rows Whose Proportion of Zero/Missing Values Exceeds this Cutoff |
|
Filter to Include Annotation Rows |
|
Filter to Include Observations |
|
Filter to Include Rows |
|
Filter to Include Secondary Annotation Rows |
|
Filtered Output Data Set Name |
|
Filtration Method for Data Points with Large Residuals |
|
First Experimental Design Data Set |
|
First Tall Data Set |
|
Fixed Effects for Differential Expression |
|
Flagging Output Data Set Name |
|
Folder of Raw Data Files |
|
Folder of Track Settings Files |
|
Format |
|
Fourth Experimental Design Data Set |
|
Fourth Tall Data Set |
|
GenBank Accession Variable |
|
Gene Description Variable |
|
Gene ID Variable |
|
Gene Length Data Set |
|
Gene Length Variable |
|
Gene Symbol Variable |
|
Gradient Convergence Criterion [1,1000000] |
|
Group Percentage for Deletion |
|
Growth Protocol |
|
Hyb Protocol |
|
ID |
|
ID Variable |
|
In Mean plots, size Error Bars using: |
|
Include adjusted p-values in addition to -log10 (p-values) |
|
Include exponentiated Estimates and Differences |
|
Include Fold Changes in Addition to Log Fold Changes |
|
Include Fold Changes in Addition to Log2 Fold Changes |
|
Include group statistics in Output Data Set |
|
Include p-values in addition to -log10 (p-values) |
|
Include simple Differences only |
|
Include Standard Errors |
|
Include t-Statistics |
|
Input data is log-transformed |
|
Input SAS Data Set |
|
Input x and y Data Set |
|
Input z Data Set |
|
Intensity Columns to Filter |
|
JMP Journal Output File |
|
JMP Script Output File Name |
|
JSL Output File |
|
Keep 0 Values without normalizing |
|
Kenward-Roger Degrees of Freedom Method |
|
Key Variable(s) to Associate with Input SAS Data Set |
|
Key Variable(s) to Merge with Input SAS Data Set |
|
Key Variables for Merging |
|
Label |
|
Label Protocol |
|
Label Variable |
|
Lambda Number |
|
Link Function |
|
List all model fits |
|
List every model fit |
|
List-Style Specification of Intensity Columns to Filter |
|
List-Style Specification of Variables |
|
List-Style Specification of Variables for Which to Display Distributions |
|
List-Style Specification of Variables to Be Standardized |
|
List-Style Specification of With Variables |
|
Loess Weight Data Set |
|
-log10(p-Value) Cutoff |
|
Log Transformation of Measurements |
|
Log transformed Output Data Set |
|
Manufacturer |
|
Manufacturer protocol |
|
Match case for key variables |
|
Maximum Dispersion to Filter Genes |
|
Maximum Filtering Loops |
|
Maximum Mean to Filter Genes |
|
Maximum Number of Principal Components to Apply |
|
Maximum z Value |
|
Merge Annotation into Residuals Data Set |
|
Merge Key Variables |
|
Merge Key Variables to Associate with Input SAS Data Set |
|
Minimum Dispersion to Filter Genes |
|
Minimum Distance Between Genotyping Groups |
|
Minimum Mean to Filter Genes |
|
Minimum Ratio Range Between 2 Homozygous Groups |
|
Minimum z Value |
|
Mixed Model Expression Index Output Data Set Name |
|
Mixed Model Output Data Set Name |
|
Mixed Model Output Data Set Prefix |
|
MMEI Output Data Set Name |
|
Molecule |
|
Multiple Testing Fixed Effects |
|
Multiple Testing Method |
|
Multipliers of Design Size |
|
New Batches from Previous Batches |
|
Normalized Response Filter Expression |
|
Number of By Groups to Process at a Time |
|
Number of Clusters |
|
Number of Density Grid Points |
|
Number of Discrete Classes to Use in Plots |
|
Number of Factors to Subtract from the Data |
|
Number of the First Principal Component for VCA |
|
Number of First Principal Component to Model |
|
Number of Last Principal Component to Model |
|
Number of LOESS Iterations |
|
Number of PLS Components |
|
Number of Principal Components |
|
Number of Random Splits |
|
Number of Rows to Process at a Time |
|
Number of Standard Deviations in Error Bars |
|
Number of Variable Genes to Keep |
|
Number of x Blocks |
|
Number of x Grid Points |
|
Number of y Blocks |
|
Number of y Grid Points |
|
Numerical Parameter for Advanced Standardization Methods |
|
Only compute overall F-Test for Fixed Effects for Differential Expression |
|
Organism |
|
Organism(s) |
|
Origin Corner |
|
Other Columns to Include |
|
Output Batch Profile Data Set |
|
Output Coordinates Data Set |
|
Output Data Set |
|
Output Data Set Containing Filtered Data |
|
Output Data Set for Graphs |
|
Output Data Set for MA Plot |
|
Output Data Set Name |
|
Output Data Set of KDMM Factors |
|
Output Data Set of Rescaling Factors |
|
Output Data Set of RPM Factors |
|
Output Data Set of TMM Factors |
|
Output Data Set of TPM Factors |
|
Output Data Set of Upper Quartile Factors |
|
Output Data Set Prefix |
|
Output Eigenvalues Data Set |
|
Output Experimental Design Data Set |
|
Output File Prefix |
|
Output File Primary Title |
|
Output File Secondary Title |
|
Output Folder |
|
Output HTML File |
|
Output Normalized Data Set |
|
Output experimental samples only |
|
Output Plotting Data Set |
|
Output Ratio Data Set |
|
Output Statistics Data Set |
|
Output Surface Data Set |
|
Output Tall Data Set |
|
Output Test Data Set |
|
Output Updated Batch Profile Data Set |
|
Output Variance Components Data Set |
|
Overall Design |
|
Overlay density estimates |
|
PCA Plot Grouping Variables |
|
PDF or RTF Output File |
|
PDF or RTF Output File Name |
|
Percentage of Data to Be Included in Training Data |
|
Percentage of Nonmissing and Nonzero Data to Be in Training Subset |
|
Percentile to Compute for PCTL Statistic |
|
Percentage of Data on A Component to Be Trimmed |
|
Percentage of Data on M Component to Be Trimmed |
|
Percentage of Data to Be Trimmed before Summary [0,50] |
|
Percentage of Mitochondria Genes Allowed |
|
Percentile to Impute |
|
Perform log2 transform after standardization |
|
Perform within-array Loess normalization |
|
Platform |
|
Platform Contributors |
|
Platform Data Set |
|
Platform Organism |
|
Platform Title |
|
Plot Rate |
|
Plot standardized residuals |
|
Plot Variable 1 Axis Label |
|
Plot Variable 2 Axis Label |
|
Plotting Variables |
|
Position Variable |
|
Prefix for Experimental Design Output Data Set Names |
|
Prefix for Tall Output Data Set Names |
|
Primary Title to use in Plots |
|
PROC FACTOR Options |
|
PROC GLIMMIX Options |
|
PROC MIXED Options |
|
PROC MIXED Statements |
|
PROC MIXED/GLIMMIX Statements |
|
PROC PLS Options |
|
Pseudo-Likelihood Convergence Criterion |
|
PubMed ID |
|
QC Data Set |
|
Random Effects |
|
Random Number Seed |
|
Random Number Seed for Picking Random Subset |
|
Randomly split the data |
|
Ratio Output Data Set |
|
Raw Data File(s) |
|
Reference Variable |
|
Reference Variable to Be Applied as the Baseline |
|
Remove duplicate columns |
|
Repeats |
|
Replace intensities falling at least this many Standard Deviations above the Column Mean |
|
Replace intensities falling at least this many Standard Deviations below the Column Mean |
|
Replace intensities falling above this column percentile |
|
Replace intensities falling above this value |
|
Replace intensities falling below this Column Percentile |
|
Replace intensities falling below this value |
|
Replace highest values |
|
Replace lowest values |
|
Rescale the data based on the total measurements in the Training data set |
|
Residual Cutoff |
|
Residual False Positive Rate |
|
Response Filter Expression |
|
Response Variable Axis Label |
|
Result Data Set |
|
RNA data is log-transformed |
|
RNA Design Variables to be Added in Output Data Sets |
|
RNA Intensity Input SAS Data Set |
|
RNA Matching Variables |
|
RNA Output Data Set |
|
Round normalized count data to integer |
|
Row Index Variable |
|
Row-Level Categorical Variables |
|
Sample Description |
|
Sample Name |
|
Scale rows |
|
Scaling Approach |
|
Scan Protocol |
|
Second Experimental Design Data Set |
|
Second Tall Data Set |
|
Secondary Annotation Chromosome Variable |
|
Secondary Annotation Label Variable |
|
Secondary Annotation Merge Variables |
|
Secondary Annotation Position Variable |
|
Secondary Annotation SAS Data Set |
|
Select Comparison Set for Differential Expression Tests |
|
Select Comparison Set for Mean Differences Tests |
|
Select Training subset based on Missing status |
|
Separate and journal results by chromosome |
|
Separate results based on Design-Level By Variables |
|
Series Title |
|
Series Variables |
|
Server Output Directory |
|
Set flagging data to Missing |
|
Set negative values to Missing before imputing |
|
Shifting Factor |
|
Shrink variances using Empirical Bayes |
|
Smoothing Bandwidth Multiplier |
|
Smoothing Parameter |
|
SNP ID Variable |
|
Sort VCA Plots by Weighted Average Proportion of Variation |
|
Source Name |
|
Split by these variables |
|
Standardization Method |
|
Standardization Method for Comparing Means |
|
Standardization Method for Difference Tests |
|
Standardization Statistics Input SAS Data Set |
|
Standardize |
|
Standardize Batch profile |
|
Standardize KDMM factor |
|
Standardize TMM Scaling Factor |
|
Standardized Residuals Output Data Set Name |
|
Statistic to Impute |
|
Study |
|
Sub-Feature Variable |
|
Subject Variable |
|
Subset Data Set to Use for Normalization |
|
Summary |
|
Summary Statistic |
|
Support |
|
Technology |
|
Third Experimental Design Data Set |
|
Third Tall Data Set |
|
Threshold |
|
Time to Event Variable |
|
Title |
|
Track Settings Files |
|
Transposed Output Data Set |
|
Treatment Protocol |
|
Type of Correlation |
|
Model Data As: |
|
Unbounded Variance Component Estimates |
|
Uniformly scale histograms in Detail plots |
|
Uniformly scale y-axes in Volcano and Chromosome Position plots |
|
Uniformly scale y-axes in Volcano plots |
|
Use pooled Estimate of Variance |
|
Value Definition |
|
Value of Columns above to Be Associated with Control |
|
Value of Columns above to Be Associated with Non-autosomes |
|
Value of the Censor Variable that Indicates Censoring |
|
Value of Variable Above to Be Used as Denominator |
|
Value to Use to Replace Highest Values |
|
Value to Use to Replace Lowest Values |
|
Value of Columns above to Be Associated with Reference |
|
Values of ID Variable to Plot |
|
Variable Containing Names of Loess Weight Data Set Columns |
|
Variable Defining the Ratio |
|
Variable Gene Selection Method |
|
Variables |
|
Variables by Which to Merge Annotation Data |
|
Variables by Which to Merge Annotation Data 1 |
|
Variables by Which to Merge Annotation Data 2 |
|
Variables By Which to Merge Filter Data Set |
|
Variables by Which to Merge Primary Annotation Data |
|
Variables by Which to Merge Secondary Annotation Data |
|
Variables Defining Analysis Groups |
|
Variables Defining Blocks |
|
Variables Defining Control Sets |
|
Variables Defining Groups |
|
Variables Defining Groups for Mean Processing |
|
Variables for Which to Display Distributions |
|
Variables to Keep in Output |
|
Variables to Be Normalized |
|
Variables to Be Standardized |
|
Variance Component Effects |
|
Variables to Include in the Imputation Process |
|
Weblink |
|
Weighted With Kernel Density |
|
Where Clause for Subsetting Input Data Set in Test Run |
|
Winsor Rate |
|
With Variables |
|
Within Sub-Feature Median |
|
Mean Difference Filter Cutoff |
|
x-Coordinate Variable |
|
y-Coordinate Variable |
|
z-Coordinate Variables |
|
Additional PROC CLUSTER Options |
|
Additional PROC DISTANCE Options |
|
Additional PROC TREE Options |
|
Alpha |
|
Annotation Chromosome Variable |
|
Annotation Column Name Variable |
|
Annotation Group Variable |
|
Annotation Label Variable |
|
Annotation Merge Variables |
|
Annotation Position Variable |
|
Annotation SAS Data Set |
|
Annotation Variables to Keep |
|
By Variables |
|
Categorical Variables |
|
Center Columns |
|
Center Rows |
|
Clustering Method |
|
Color row profiles by: |
|
Color Theme for Heat Map |
|
Color Variable |
|
Compare Variables |
|
Compute Covariances Instead of Correlations |
|
Compute Pearson covariances instead of correlations |
|
Compute results for annotated rows only |
|
Continuous Variables |
|
Correlation Radius for Clustering |
|
Covariates for Partial Correlations |
|
Cutoff Level of Tree Axis |
|
Design Color Variables |
|
Design Label Variable |
|
Display clustered heat map |
|
Distance Metric |
|
Distance Variables |
|
Double center multiplicatively |
|
Experimental Design SAS Data Set |
|
Filter to Include Annotation Rows |
|
Filter to Include Observations |
|
Filter to Include Observations from the Primary Data Set |
|
Filter to Include Observations from the Secondary Data Set |
|
Filter to Include Primary Variables |
|
Filter to Include Secondary Variables |
|
GenBank Accession Variable |
|
Gene Description Variable |
|
Gene ID Variable |
|
Gene Symbol Variable |
|
Group Percentage for Row Inclusion |
|
Hierarchical Clustering Method |
|
ID Variable |
|
ID Variables |
|
Impute missing values for clustering |
|
Include 3D plots |
|
Include rows if: |
|
Include rows with Interquartile Range satisfying this expression |
|
Include rows with Mean satisfying this expression |
|
Include rows with Median satisfying this expression |
|
Include rows with Percentile satisfying this expression |
|
Include rows with Standard Deviation satisfying this expression |
|
Increment Between Lower and Upper Values |
|
Input SAS Data Set |
|
Input Data Set is a Distance Matrix |
|
Intensity Columns to Plot |
|
JMP Script Output File Name |
|
JSL Output File |
|
K-Means Clustering Method |
|
Label Variable |
|
Level of Measurement |
|
List every model fit |
|
List-Style Specification of Categorical Variables |
|
List-Style Specification of Continuous Variables |
|
List-Style Specification of Covariates for Partial Correlations |
|
List-Style Specification of Distance Variables |
|
List-Style Specification of Intensity Columns to Plot |
|
List-Style Specification of Primary Set of Variables |
|
List-Style Specification of Secondary Set of Variables |
|
List-Style Specification of Variables to Compute Distances/Clustering Across |
|
List-Style Specification of Variables to Plot |
|
List-Style Specification of Variables Whose Rows Are to Be Clustered |
|
-log10(p-Value) Cutoff |
|
-log10(p-Value) Cutoff for Output Test Data Set |
|
Lower Number of Dimensions to Fit |
|
Maximum Number of Clusters |
|
Merge Key Variables |
|
Multiple Testing Method for Output Test Data Set |
|
Number of Clusters |
|
Number of Primary Set of Variables to Process at a Time (log10 Scale) |
|
Number of Principal Components |
|
Number of Secondary Set of Variables to Process at a Time (log10 Scale) |
|
Number of Variables to Process at a Time |
|
Numerical Parameter for Advanced Standardization Methods |
|
Options to Define Cluster Membership |
|
Ordering Variable |
|
Organism |
|
Output Data Set |
|
Output Data Set Name |
|
Output Data Set Prefix |
|
Output File Prefix |
|
Output Folder |
|
Output Means Data Set |
|
Output Test Data Set |
|
Percentile to Compute for PCTL Statistic |
|
Perform SAS-based clustering on the Distance Matrix |
|
Plot |
|
Plot clusters |
|
Prefix for Naming Output Variables |
|
Primary Annotation SAS Data Set |
|
Primary Input SAS Data Set |
|
Primary Set of Variables |
|
PROC CORR Statement Options |
|
PROC FASTCLUS Options |
|
PROC MDS Options |
|
PROC PLS Options |
|
Process Group Size for Primary Variables |
|
Process Group Size for Secondary Variables |
|
Replace cluster means with representative observations |
|
Scale columns |
|
Scale rows |
|
Secondary Annotation Column Name Variable |
|
Secondary Annotation SAS Data Set |
|
Secondary Annotation Variables to Keep |
|
Secondary Input SAS Data Set |
|
Secondary Set of Variables |
|
Server Output Directory |
|
SNP ID Variable |
|
Standardization Method |
|
Standardize variables before clustering |
|
Study |
|
Two Way Clustering |
|
Type of Correlation |
|
Upper Number of Dimensions to Fit |
|
Use lower boundary constraint of 0 for K matrix covariance parameter |
|
Variable to Define Tree Axis |
|
Variables By Which to Merge Annotation Data |
|
Variables by Which to Merge Annotation Data |
|
Variables Defining Groups |
|
Variables to Compute Distances/Clustering Across |
|
Variables to Keep in Output |
|
Variables to Keep in Output Data Set |
|
Variables to Plot |
|
Variables to Retain in Output Data Set |
|
Variables Whose Rows are to Be Clustered |
|
Weight Variable |
|
Absolute Mean Difference Cutoff for Continuous Predictors |
|
Absolute Proportion Difference Cutoff for Class Predictors |
|
Add reflected y variable to binary model |
|
Algorithm |
|
Annotation SAS Data Set |
|
Apply adaptive weights |
|
Asymmetric Loss Evaluation Proportion |
|
Asymmetric Loss Fitting Proportion |
|
Automated Model Type |
|
Average Pool Size |
|
Binary Dependent Variable Event Value |
|
Binary Target Variable Event Value |
|
Block Partition Variable |
|
Boosted Fraction of Training Observations in a Single Tree |
|
Boosted Maximum Number of Iterations |
|
Boosted or Forest Random Number Seed |
|
Boosted Shrinkage Factor |
|
Categorical Covariates |
|
Categorical Variables |
|
Censor Variable |
|
Centroid or Distance Summarization Method |
|
Change output folder in Settings moved to right panel |
|
Chromosome ID |
|
Chromosome Label |
|
Chromosome Number |
|
Color Variable |
|
Color Variables |
|
Combined Output Data Set Name |
|
Compute Individual Model Fits |
|
Compute near optimal low-rank randomized SVD for the additive and dominance matrices |
|
Continuous Covariates |
|
Continuous Variables |
|
Correlation Radius for Clustering |
|
Criterion for Stopping Model Selection |
|
Current Review |
|
Custom Costs |
|
Custom Prior Probabilities |
|
CV Partitioning Method |
|
Data Columns to be Transposed |
|
Data Step Statements |
|
Degrees of Freedom Hyper-parameter |
|
Dependent Categorical Variable |
|
Dependent Class Variable |
|
Dependent Variable |
|
Dependent Variables |
|
Display Frobenius Measure |
|
Distance Metric for Analysis |
|
Distance Metric |
|
Distribution |
|
Early Stopping Threshold |
|
Elastic Net L2 Penalty |
|
Expected Proportion of Variance Explained by the Regression Model |
|
Experimental Design Data Set |
|
Experimental Design SAS Data Set |
|
Feature Selection Criterion |
|
Filter for BLUP Coefficients |
|
Filter for PLS Coefficients |
|
Filter to Include Markers |
|
Filter to Include Observations |
|
Filter to Include Predictor Categorical Variables |
|
Filter to Include Predictor Continuous Variables |
|
Fixed Effects |
|
Fixed Test Data Set |
|
Fixed Test Set |
|
Folder of CVMC Results 1 |
|
Folder of CVMC Results 2 |
|
Folder of CVMC Results 3 |
|
Folder of CVMC Results 4 |
|
Folder of CVMC Results 5 |
|
Folder of Predictive Modeling Settings |
|
Folder of Settings Files |
|
Folder of Test Data Sets |
|
Folder of Test Sets |
|
For Nominal Dependent Variables, compute distances to: |
|
For Nominal Target Variables, compute distances to: |
|
Forest Max Number of Variables to Compute Predictor Importance |
|
Forest Max Number of Variables to Consider for Splitting a Node |
|
Forest Maximum Number of Trees |
|
Forest: Output filtered predictors list |
|
Generate HTML Output |
|
Group Variable |
|
Grouping Variable |
|
Groups Variable |
|
Heterogeneous Variance Components |
|
Hold-Out Method |
|
Hold-Out Size, Specify as: |
|
ID Variable |
|
ID Variables |
|
Impute zeros for missing continuous predictor values |
|
Impute zeros for missing values |
|
Include 3D plots |
|
Include Dominance Effects |
|
Increase R Software memory limit |
|
Inner Loop Algorithm |
|
Input SAS Data Set |
|
Input Tall Data Set |
|
Input Wide Data Set |
|
Iteration End Number |
|
Iteration Start Number |
|
JMP Script Output File Name |
|
K for K-Fold CV |
|
K for K-Fold or 1/K Hold-Out |
|
Kernel Function |
|
Kernel Function for Computing Posterior Probabilities |
|
L for Leave-L-Out |
|
L1 Regularization Parameter |
|
L2 Regularization Parameter |
|
Label Variable |
|
Link Function |
|
List every model fit |
|
List SAS Output for all model fits |
|
List-Style Specification of Continuous Variables |
|
List-Style Specification of Data Columns to be Transposed |
|
List-Style Specification of Lock-In Categorical Predictor Variables |
|
List-Style Specification of Lock-In Class Predictor Variables |
|
List-Style Specification of Lock-In Continuous Predictor Variables |
|
List-Style Specification of Lock-In Marker Variables |
|
List-Style Specification of Marker Variables |
|
List-Style Specification of Pedigree Relationship Matrix Variables |
|
List-Style Specification of Predictor Categorical Variables |
|
List-Style Specification of Predictor Continuous Variables |
|
List-Style Specification of Variables to Be Standardized |
|
Lock-In Categorical Predictor Variables |
|
Lock-In Class Predictor Variables |
|
Lock-In Continuous Predictor Variables |
|
Lock-In Marker Variables |
|
-log10(p-Value) Cutoff |
|
log10 Regularization Parameter |
|
Lower Bound for Target Variable |
|
Marker Label |
|
Marker Physical Position |
|
Marker Position |
|
Marker Variables |
|
Max Number of Categories Allowed in a Predictor |
|
Max Number of Effects in the Model |
|
Max Number of Variables to Consider for Splitting a Node |
|
Maximum Depth of Tree |
|
Maximum Number of Buckley-James Iterations |
|
Maximum Number of Filtered Predictors |
|
Maximum Number of Grid Nodes to Use |
|
Maximum Number of K-Means Clusters / Predictors |
|
Maximum Number of Predictors to Use |
|
Maximum Number of Steps |
|
Maximum Number of Trees |
|
Maximum Number of Variables to Select with Model Averaging |
|
Maximum Number of Variables to Select with Pooling |
|
Maximum Order of Interactions |
|
Maximum Size of Training Set |
|
Maximum Time for Area under Survival Curves |
|
Method |
|
Metric |
|
Minimum Number of Observations Required for a Branch |
|
Minimum Number of Observations Required for a Categorical Value |
|
Minimum Size of Training Set |
|
Minimum Time for Area under Survival Curves |
|
Mode |
|
Model Selection Method |
|
Multiple Testing Method |
|
Nominalize Continuous Dependent Variables |
|
Number of Burn In Samples |
|
Number of Generations |
|
Number of Grid Points for Each Learning Curve |
|
Number of Iterations |
|
Number of model averaging samples |
|
Number of Nearest Neighbors |
|
Number of PLS Components |
|
Number of power iterations (q) for the randomized SVD |
|
Number of Predictor Variables to Select |
|
Number of Predictors Included in Model |
|
Number of Principal Components |
|
Number of Random Hold-Out Iterations |
|
Number of Random Iterations |
|
Number of Rounds of Selection |
|
Number of Rows in Input Data to Use in Test Run |
|
Number of BLUPs to Use in Prediction |
|
Number of Subsets Containing a Particular Variable |
|
Numerical Parameter for Advanced Standardization Methods |
|
Optimize the continuous predictor set |
|
Outer Loop Test Set |
|
Output Data Set |
|
Output Data Set Name |
|
Output Data Set Prefix |
|
Output Experimental Design Data Set |
|
Output Folder |
|
Output Tall Data Set |
|
Output Wide Data Set |
|
P for P-Percent-Hold-Out |
|
Pedigree Relationship Matrix Variables |
|
Perform Buckley-James Estimation |
|
Perform Cross Validation Model Comparison |
|
Perform Learning Curve Model Comparison |
|
Perform model averaging |
|
Perform poolwise selection |
|
Perform recoding with respect to: |
|
Plot Separate Charts |
|
Plot weights for predictor variables |
|
Predictor Categorical Variables |
|
Predictor Continuous Variables |
|
Prefix for Tall Column Names |
|
Prefix for Wide Column Names |
|
Primary Input SAS Data Set |
|
Primary Output Data Set Name |
|
Prior Probabilities / Prevalences |
|
PROC DISCRIM Options |
|
PROC DISTANCE Options |
|
PROC GENESELECT Statement Options |
|
PROC GLIMMIX Additional Statements |
|
PROC GLIMMIX Class Variables |
|
PROC GLIMMIX Fixed Effects |
|
PROC GLIMMIX MODEL Statement Options |
|
PROC GLIMMIX Statement Options |
|
PROC GLMSELECT Modeling Options |
|
PROC GLMSELECT Statement Options |
|
PROC HPMIXED Additional Statements |
|
PROC HPMIXED Class Variables |
|
PROC HPMIXED Fixed Effects |
|
PROC HPMIXED MODEL Statement Options |
|
PROC HPMIXED Statement Options |
|
PROC LIFEREG Modeling Options |
|
PROC LIFEREG Statement Options |
|
PROC LOGISTIC MODELING Options |
|
PROC LOGISTIC Response Options |
|
PROC LOGISTIC Statement Options |
|
PROC MIXED Additional Statements |
|
PROC MIXED Class Variables |
|
PROC MIXED Fixed Effects |
|
PROC MIXED MODEL Statement Options |
|
PROC MIXED Statement Options |
|
PROC PHREG Modeling Options |
|
PROC PHREG Statement Options |
|
PROC PLS Statement Options |
|
PROC QUANTSELECT Statement Options |
|
PROC QUANTSELECT Modeling Options |
|
Quantile Level |
|
Quantile Level for Quantile Regression |
|
R Software Memory Size (Mb) |
|
Random Number Seed |
|
Random Number Seed for Forest |
|
Random Number Seed for Randomize SVD |
|
Reference Time for Comparing Survival Curves |
|
Reference Times for Comparing Survival Curves |
|
Regard missing values as valid for prediction |
|
Regression Model |
|
Root Mean Square Error Convergence Tolerance |
|
Rule Mix Maximum Number of Initial Rules |
|
Rule Mix Maximum Number of Secondary Rules |
|
SAS Procedure |
|
Scale Hyper-parameter |
|
Secondary Input SAS Data Set |
|
Secondary Output Data Set Name |
|
Separate Bar Charts for Each Model |
|
Separate Bar Charts for Each Test Set |
|
Separate Charts for Each Model |
|
Separate Charts for Each Test Set |
|
Server Output Directory |
|
Settings Files |
|
Settings for Which to Construct Learning Curves |
|
Settings to Cross Validate |
|
Settings to Use for Test Data Set Evaluation |
|
Settings to Use for Test Set Evaluation |
|
Significance Level for Adding Variables |
|
Significance Level for Keeping Variables |
|
Significance Level for Retaining Variables |
|
Similarity Measure |
|
SL for Adding Variables |
|
SL for Keeping Variables |
|
SL for Retaining Variables |
|
Standardization Method for Predictor Continuous Variables |
|
Standardize Predictors Row-Wise |
|
Statistical Testing Method for Continuous Predictors |
|
Study |
|
Target Categorical Variable |
|
Target rank (k) of the low-rank randomized SVD |
|
Target Variable |
|
Target Variables |
|
Test Data Set |
|
Test Data Sets |
|
Test Sets |
|
Thinning Rate |
|
Time to Event Variable |
|
Transformation for Predictor Continuous Variables |
|
Type of Dependent Variable |
|
Type of Target Variable |
|
Upper Bound for Target Variable |
|
Usage of K-Means Clusters |
|
Use Forest to create interaction indicators |
|
Use Forest to filter predictors |
|
Use Grid Computing |
|
Use life regression to filter predictors |
|
Use K-Means clustering to reduce predictors |
|
Use Leave-One-Out error rate as the Fitness function |
|
Use PROC HPLOGISTIC |
|
Use simple Cox Proportional Hazards function to filter predictors |
|
Use statistical testing to filter predictors |
|
Validation Data Set |
|
Value of the Censor Variable that Indicates Censoring |
|
Values of the Censor Variable that Indicate Censoring |
|
Variable Selection Method |
|
Variables Defining Tall Column Names |
|
Variables Defining Wide Column Names |
|
Variables to Be Standardized |
|
Weight for Censored Observations |
|
Weight Variable |
|
Weighting Function |
|
Where Clause for Subsetting Input Data in Test Run |
|
Alpha |
|
Apply adaptive weights |
|
Categorical Clustering Variables |
|
Class Clustering Variables |
|
Cluster Effect Type |
|
Continuous Clustering Variables |
|
Criterion for Stopping Model Selection |
|
CV Partitioning Method |
|
Dependent Variable |
|
Direction of Enhanced Treatment Effect |
|
Fixed Main Effects |
|
Input SAS Data Set |
|
JMP Script Output File Name |
|
K for K-Fold CV |
|
List-Style Specification of Categorical Clustering Variables |
|
List-Style Specification of Class Clustering Variables |
|
List-Style Specification of Continuous Clustering Variables |
|
List-Style Specification of Predictor Categorical Variables |
|
List-Style Specification of Predictor Continuous Variables |
|
Main Effects Selection Method |
|
Max Number of Variables to Consider for Splitting a Node |
|
Maximum Depth of Tree |
|
Maximum Number of Steps |
|
Maximum Number of Trees |
|
Maximum Order of Interactions |
|
Minimum Number of Observations Required for a Branch |
|
Minimum Number of Observations Required for a Categorical Value |
|
Model Selection Method |
|
Number of Bins for Continuous Variables |
|
Number of Principal Components to Use for Propensity Scoring |
|
Number of Resamples to Use for Computing Significance |
|
Output Data Set Prefix |
|
Output Folder |
|
Predictor Categorical Variables |
|
Predictor Continuous Variables |
|
Random Number Seed |
|
Random Number Seed for Forest |
|
Regard missing values as valid for prediction |
|
Relaxation Factor for Alpha |
|
SL for Adding Variables |
|
SL for Keeping Variables |
|
Study |
|
Target Variable |
|
Treatment Control Level |
|
Treatment Variable |
|
Type of Dependent Variables |
|
Use Interactions between treatment and predictor variables |
|
Variable Selection Method |
|
Variability Assumption |
|
Weight Variable |
|
Adjust all p-value variables together |
|
Alpha |
|
Annotation SAS Data Set |
|
Annotation Merge Variables |
|
Category Variable |
|
Censor Limit (-log10 scale) |
|
Censor Limit (-log or -log10 scale) |
|
Create significance indicator columns |
|
Effect Estimate or Direction Variable |
|
Effect Estimate or Direction Variable is the odds ratio |
|
Effect ID Variable |
|
Filter to Include Annotation Rows |
|
Filter to Include Observations |
|
Folder of Input SAS Data Sets |
|
ID Variable |
|
Input SAS Data Set |
|
Method to Use |
|
Multiple Testing Method |
|
Open Output Data Set |
|
Other Effect Variables |
|
Other ID Variables |
|
Other p-Value Variables |
|
Other Sample Size Variables |
|
Other Standard Error Variables |
|
Output Data Set |
|
Output File Prefix |
|
Output Folder |
|
Output rows with a significant p-value only |
|
p-Value Combination Method |
|
p-Value Variable |
|
p-Value Variables |
|
Primary Delimiter Separating Annotation Categories |
|
Sample Size Variable |
|
SAS Data Sets |
|
Secondary Delimiter |
|
Server Output Directory |
|
Standard Error Variable |
|
Study |
|
Study ID Variable |
|
Tau Value for TPM |
|
Transformation of Input p-Values |
|
Transformation of Output Adjusted p-Values |
|
Transformation of Output p-Values |
|
Variables By Which to Merge Annotation Data |
|
-log10(p-value) Cutoff |
|
Additional Bandwidth on Each Side of Tracks |
|
Alpha |
|
Annotation Merge Variables |
|
Annotation SAS Data Set |
|
Annotation Variables to Keep |
|
Bin Method |
|
Bin Summary Statistic |
|
Chromosome |
|
Chromosome Color Theme Settings File |
|
Chromosome Text Data Set |
|
Chromosome Text File |
|
Chromosome Variable |
|
Chromosome Variable 1 |
|
Chromosome Variable 2 |
|
Coding Region End |
|
Coding Region Start |
|
Color of Bars ({r,g,b}) |
|
Color Theme |
|
Color Variable |
|
Color Variable Type |
|
Construct Color Theme using: |
|
Continuous Variables to Plot |
|
Create separate plots for each variable |
|
Custom Track Variable |
|
Description |
|
Direction of Other Variables |
|
Display output as a: |
|
Circular Display |
|
Draw indicator line |
|
End |
|
Exon Count |
|
Exon Ends |
|
Exon Starts |
|
Filter to Include Annotation Rows |
|
Filter to Include Observations |
|
Folder of Chromosome Color Theme Settings Files |
|
Folder of Track Settings Files |
|
GenBank Accession Variable |
|
Gene Description Variable |
|
Gene Name or Identifier |
|
Gene ID Variable |
|
Gene Symbol Variable |
|
Genome |
|
Initial Color Theme |
|
Initial Cutoff for Displaying Bars |
|
Input GFF File |
|
Input SAS Data Set |
|
Label for Other Variables |
|
Label |
|
Label Variable |
|
Lightness Scale |
|
Links Color Theme |
|
Links Color Variable |
|
Links Input SAS Data Set |
|
Multiple Testing Method |
|
Name |
|
Number of Legend Decimals |
|
Number of Legend Levels |
|
Number of Rows in Each Bin |
|
Organism |
|
Output Data Set |
|
Output Folder |
|
Plot bars |
|
Plot markers with significant p-values only |
|
Position |
|
Position Variable |
|
Position Variable 1 Start |
|
Position Variable 1 Stop |
|
Position Variable 2 Start |
|
Position Variable 2 Stop |
|
Primary Color |
|
Reverse Color Theme |
|
Saturation Scale |
|
Search Type |
|
Secondary Color |
|
Server Output Directory |
|
Set window size |
|
SNP ID Variable |
|
Start |
|
Strand |
|
Study |
|
Summary Statistic Across Continuous Variables |
|
Text Data Set |
|
Text File |
|
Threshold Indicator |
|
Title of Custom Track |
|
Track Settings Files |
|
Transformation of Input p-Values |
|
Transformation of Output p-Values |
|
Transparency |
|
Two Column Threshold |
|
Type of Continuous Variables to Plot |
|
Value at Which to Censor High Values |
|
Value at Which to Censor Low Values |
|
Value Ordering for Nominal Variables |
|
Values at Which to Draw Horizontal Reference Lines |
|
Variables By Which to Merge Annotation Data |
|
Variables to Keep in HTML Data Set |
|
Variables to Retain in HTML Data Set |
|
Width of Bars |
|
Width of Positional Bin |
|
Window Size |
|
y Variable |
|
y Variables |
|
-log10(p-Value) Cutoff |
|
Affymetrix Array Type |
|
Affymetrix GeneChip Array |
|
Affymetrix Link |
|
Agilent Array Type |
|
Alpha |
|
AmiGO Database Link |
|
Annotation Merge Variables |
|
Annotation SAS Data Set |
|
Annotation Variables to Keep |
|
Applied BioSystems Array Type |
|
Categorical Phenotype Variable |
|
Category Variable |
|
Category Variables |
|
Check uniqueness of column names |
|
Chromosomal Location |
|
Chromosome |
|
Codelink Array Type |
|
Compress output data sets |
|
Continuous Phenotype Variables |
|
Control Levels |
|
Custom Track Variable |
|
Data Step Statements |
|
dbSNP ID |
|
dbSNP Link |
|
Description |
|
Direction of Significance Variables |
|
EC Database Link |
|
End |
|
Enrichment Tests |
|
Ensembl Database Link |
|
Ensembl ID |
|
Entrez Gene ID |
|
Entrez Databases Link |
|
Entrez Gene Link |
|
Entry Delimiter |
|
Entry Id Delimiter |
|
Enzyme ID (EC number) |
|
Experimental Design SAS Data Set |
|
Files to Import |
|
Filter to Include Annotation Rows |
|
Filter to Include Observations |
|
Folder of List Files |
|
Folder of Raw Files |
|
GenBank Accession |
|
GenBank Link |
|
Gene Description |
|
Gene Description Variable |
|
Gene ID |
|
Gene Identifier Variable |
|
Gene Name or Identifier |
|
Gene Name Variable |
|
Gene/Protein Identifier |
|
Gene Set Summary Method |
|
Gene Symbol |
|
Genome |
|
GO ID |
|
HGNC (Gene Symbol) Database Link |
|
High Color RGB |
|
High Hit Total Threshold |
|
Homologene |
|
ID Variable |
|
Illumina Array Type |
|
Ingenuity Canonical Pathway Membership Data (CSV file) |
|
Ingenuity knowledge Base |
|
Ingenuity Server |
|
Input GMT File of Gene Sets |
|
Input SAS Data Set |
|
IPA Entry Point |
|
IPA Project Name |
|
JSL Output File |
|
List Description File |
|
Low Color RGB |
|
Low Hit Threshold |
|
Map Viewer Database Link |
|
Maximum Category Length |
|
Maximum Column Length |
|
Method for Computing Reference Level for Each Gene |
|
Middle Color RGB |
|
Multiple Testing Method for Adjusting p-Values |
|
Number of Bins for Cochran-Armitage Tests |
|
Number of Bootstrap or Permutation Samples |
|
Number of Genes to Process at a Time |
|
Number of Rows to Scan |
|
OMIM Database Link |
|
OMIM ID |
|
Organism |
|
Organism-specific code |
|
Output Data Set |
|
Output Data Set Containing Categories |
|
Output Data Set Containing Category Indicators |
|
Output Data Set Containing Statistics |
|
Output Data Set Name |
|
Output File Name |
|
Output File Type |
|
Output Folder |
|
Parse associated gene column |
|
Percentile to Use as the Highest Color Value |
|
Percentile to Use as the Lowest Color Value |
|
Platform |
|
Prefix for Output Data Set Names |
|
Primary Delimiter Separating Annotation Categories |
|
Probe ID |
|
Probe Set or Gene ID |
|
PubMed Database Link |
|
Random Number Seed |
|
Rank Transform Continuous Significance Variables for PAGE Tests |
|
Reference Sequence Database Link |
|
RefSeq ID |
|
Row Reference Summary Statistic |
|
Secondary Delimiter |
|
Server Output Directory |
|
Set window size |
|
Significance Cutoff |
|
Significance Input SAS Data Set |
|
Significance Variable |
|
Significance Variable Cutoff for Fisher Exact Tests |
|
Significance Variables |
|
Specify up to 20 IPA observations to upload |
|
Standardize Rows based on Reference Group Standard Deviation |
|
Start |
|
Study |
|
Swiss-Prot Database Link |
|
Swiss-Prot ID |
|
Title of Custom Track |
|
Title of Custom Track |
|
Type |
|
Type of Gene Identifier |
|
UniGene ID |
|
UniGene Link |
|
Use a proxy server to access the Web |
|
Variables by Which to Color Pathways |
|
Variables By Which to Merge Annotation Data |
|
Variable Containing IDs |
|
Variables Defining Analysis Groups |
|
Variables Defining Control Sets |
|
Variables to Keep in Gene-Level Output |
|
Variables to Keep in Output |
|
Variables to Retain in HTML Data Set |
|
Window Size |
|
0-1 Variables |
|
Access Documentation from the: |
|
Add Filter Columns |
|
Additional Fixed Effects |
|
Additional PROC MIXED Statements |
|
Additional SAS Data Step Statements |
|
Affymetrix Array Type |
|
Agilent Array Type |
|
Alpha Values |
|
Append Input Data Set |
|
Append Input SAS Data Set |
|
Applied BioSystems Array Type |
|
Apply Original Column Names |
|
Archive the resolved SAS macro code |
|
Archive the SAS code |
|
Array Variable |
|
Auto clear |
|
Base Input Data Set |
|
Base Input SAS Data Set |
|
Base SAS Data Set |
|
By Variables |
|
Categorical Variables |
|
Channel Variable |
|
Check uniqueness of column names |
|
Codelink Array Type |
|
Column Name Variable |
|
Column Order Data Set |
|
Column Variables |
|
Compare Parameters Data Set |
|
Compress output data set |
|
Compress output data sets |
|
Concatenate SAS Data Sets |
|
Constant to Apply |
|
Constants for Each Variance Component |
|
Control Levels for Differential Expression Comparisons |
|
Corresponding Key Variables from Merge Input Data Set |
|
Corresponding Key Variables from Merge Input SAS Data Set |
|
Data Columns to be Transposed |
|
Data Set of Differences to Include from Comparison Set |
|
Data Start Row |
|
Data Step Statements |
|
Default Annotation Folder |
|
Default Input Folder |
|
Default Library Folder |
|
Default Narrative Template Folder |
|
Default Output Folder |
|
Default Server Output Directory |
|
Default Settings Folder |
|
Default Template Name |
|
Delete nonmatching rows |
|
Delete rows not in Base Input Data Set |
|
Delete rows not in Base Input SAS Data Set |
|
Delete rows satisfying this expression |
|
Delete rows with at least this percentage of Missing values |
|
Display Pre-Study Variable Requirements in terms of: |
|
Drop numeric variables used to compute statistics |
|
Drop Variables |
|
Effect Sizes |
|
Experimental Design Data Set |
|
Experimental Design SAS Data Set |
|
File Containing Estimate Statements |
|
File Filter Expression |
|
File Type |
|
Files to Import |
|
Filter to Include Observations |
|
Filter to Include Observations (1) |
|
Filter to Include Observations (2) |
|
Filter to Include Observations (3) |
|
Filter to Include Observations (4) |
|
Filter to Include Tall Rows (and the corresponding Wide Variables) |
|
Filter to Keep Observations |
|
First Folder of Data Sets to Compare |
|
Fixed Effects for Differential Expression |
|
Folder Containing SAS Data Sets |
|
Folder for UTF-8 Files after Converting |
|
Folder of Non-UTF-8 Files |
|
Folder of Raw Files |
|
Force Append |
|
Format |
|
Frequency Variable |
|
Gene/Protein Identifier |
|
Hide reports with unsatisfied study requirements from Starter |
|
Hide unchosen dialog options from requirements report |
|
Hide unsatisfying studies from report dialogs |
|
ID Variables |
|
Illumina Array Type |
|
Include |
|
Include observations that meet: |
|
Ingenuity Knowledge Base |
|
Ingenuity Server |
|
Input Data Set |
|
Input Data Step Statements |
|
Input SAS Data Set |
|
Input Tall Data Set |
|
Input Wide Data Set |
|
IPA Entry Point |
|
IPA Project Name |
|
JMP Script Output File Name |
|
Keep labels |
|
Key Variables from Base Input Data Set |
|
Key Variables from Base Input SAS Data Set |
|
List of Variable Names and Lengths |
|
List of Variable Names and Types |
|
List-Style Specification of Data Columns to Be Transposed |
|
List-Style Specification of Numeric Variables |
|
List-Style Specification of Transpose Variables |
|
List-Style Specification of Variables to Be Standardized |
|
List-Style Specification of Variables to Be Summarized |
|
List-Style Specification of Variables to Be Transformed |
|
List-Style Specification of Variables to Reorder |
|
List-Style Specification of Wide Variables Corresponding to Tall Rows |
|
Match case for key variables |
|
Maximum Column Length |
|
Maximum Length for All Other (Unselected) Variables |
|
Merge Input Data Set |
|
Merge Input SAS Data Set |
|
Merge Key Variables |
|
Merge Key Variables (Venn Diagram - Multiple Tables) |
|
Merge Key Variables to Associate with Input SAS Data Set |
|
Metadata Server Name |
|
Method for Handling Ties |
|
Minimize lengths of selected variables |
|
Minimum Number of Columns to Scan |
|
Multipliers of Design Size |
|
Name |
|
Name of Response Variable |
|
Name of this Settings Profile |
|
New Label Specifications |
|
New Length for Selected Variables |
|
New Variable Names |
|
Number of Columns to Use in Subset |
|
Number of Groups for Rank Method GROUPS |
|
Number of Rows to Scan |
|
Numeric Variables over Which to Compute Row Statistics |
|
Numerical Parameter for Advanced Standardization Methods |
|
Output Data Set |
|
Output Data Set for Graphs |
|
Output Data Set Name |
|
Output Data Step Statements |
|
Output Experimental Design Data Set |
|
Output Experimental Design Data Set Name |
|
Output File |
|
Output File Name |
|
Output Folder |
|
Output Stack Data Set |
|
Output Statistics Data Set |
|
Output Tall Data Set |
|
Output Wide Data Set |
|
Password |
|
Percentile to Compute for PCTL Statistic |
|
Percentile to Impute |
|
Perform log2 transform after standardization |
|
Platform |
|
Port Number |
|
Prefix |
|
Prefix for Column Names in Tall Data Set |
|
Prefix for Output Data Set Names |
|
Prefix for Tall Column Names |
|
Prefix for Wide Column Names |
|
Pre-SET Data Step Statements |
|
Pre-SET Output Data Step Statements |
|
Print Options |
|
PROC MIXED Options |
|
Prompt about closing all associated graphics and tables when closing tabbed reports |
|
Proportional Areas |
|
Proportional Surrounding Area (applies only for 1-way, 2-way, and 3-way diagrams) |
|
Proxy Port Number |
|
Proxy Server Name |
|
Random Effects |
|
Random Number Seed |
|
Rank Method |
|
Rank Order |
|
Rank Variables |
|
Remove labels from these variables |
|
Remove rows with duplicate values of Sort Variables |
|
Remove variables not found |
|
Replace value of counts with proportion of total counts |
|
Repository Name |
|
Response Variable |
|
Row Number of Variable Names |
|
Row Variables |
|
SAS Code for Transformation |
|
SAS Data Set Folder |
|
SAS Drug Development Server URL |
|
SAS File Folder |
|
Save and Restore Current Row States |
|
Second Folder of Data Sets to Compare |
|
Select |
|
Select Columns |
|
Select Comparison Set for Differential Expression Tests |
|
Select Missing |
|
Server Output Directory |
|
Set negative values to Missing before imputing |
|
Shared Grid Folder (UNC path recommended) |
|
Shared Grid Folder - Client Version |
|
Shared Grid Folder - Server Version |
|
Shifting Factor |
|
Show |
|
Show Starter Customization buttons |
|
Show Variable Requirements and Usage link on report dialogs |
|
Sort |
|
Sort Variables |
|
Specify a name for the 0-1 column |
|
Specify up to 20 IPA observations to upload |
|
Standardization Method |
|
Standardization Statistics Input SAS Data Set |
|
Standardize |
|
Starting Values for 3-Way Optimization |
|
Statistic to Compute |
|
Statistic to Impute |
|
Statistics to Compute |
|
Study |
|
Subset Data Set to Use for Normalization |
|
Summary Statistic to Compute for Each Variable |
|
Tall SAS Data Set |
|
Transform Expression |
|
Transport File Folder |
|
Transport File Name |
|
Transpose Variables |
|
Transposed Output Data Set |
|
Type |
|
Type of Transformation |
|
Use a subset of columns |
|
Use Only Selected Rows when Comparing Tables |
|
User Name |
|
Variable Containing Current Column Names |
|
Variable Containing Names of Wide Variables |
|
Variable Containing New Column Names |
|
Variable to Identify Individual Probe Set |
|
Variables By Which to Summarize |
|
Variables Defining Groups |
|
Variables Defining Tall Column Names |
|
Variables Defining Wide Column Names |
|
Variables to Be Standardized |
|
Variables to Be Summarized |
|
Variables to Be Transformed |
|
Variables to Drop |
|
Variables to Drop from Output SAS Data Set |
|
Variables to Exclude from the Output Stack Data Set |
|
Variables to Include in the Imputation Process |
|
Variables to Keep in Output Data Set |
|
Variables to Keep in Output SAS Data Set |
|
Variables to Reorder |
|
Variables to Retain in Output Data Set |
|
Variables Whose Length is to be Changed |
|
Version of SDD instance: |
|
Weight Variable |
|
Wide SAS Data Set |
|
Wide Variables Corresponding to Tall Rows |
|
Using JMP Graphics in Presentations and Publications |
|
Specifying Folders, Files, and Data Sets |
|
Examining Folders, Files, and Data Sets |
|
List-Style Specification |
|
The SAS WHERE Expression |
|
Estimate Statements and the Estimate Builder |
|
Rules for Study Names |
|
Rules for Paths |
|
Rules for Review Package Names |
|
JMP Genomics Files are Identified by Suffixes |
|
JMP Genomics Processes Call SAS PROCS |
|
Glossary |
|
Trouble Shooting |
|
References |
|
What do I need?
A JMP table containing at least one column of p-values of an arbitrary set of features (for example, genes, probesets, exons, markers) must be open and in focus before you can select and open the P-Value Quantile Plotter dialog.
For detailed information about the files and data sets used or created by JMP Genomics software, see Files and Data Sets.
Output/Results
Running this process adds a column (for each P-value variable specified) containing the transformed, observed p-values to the input data set and generates a plot (shown below) of the observed p-values versus the expected p-values for this data set.
The plot for the expected p-values is represented by the solid line running diagonally upward from the lower left. The observed -log10 p-values for these data are plotted with solid black dots. The observed p-values extending away from the reference line on the right hand side are the ones representing significant differences.