JMP^® Screenshots

JMP - Create a variety of bar charts and add error bars, with the interactive Graph Builder.

JMP - Box plots and other types of graphs are available from Graph Builder.

JMP - Visualize changes over time using Bubble Plots.

JMP - Analyze process capability using the Distribution platform.

Build custom menus to quickly access your data or custom applications.

Analyze complex surveys with complete control of question structures, report presentation and statistical tests performed.

The advanced neural network capabilities in JMP Pro include the choice of three activation functions and two layers, a choice of validation methods, as well as gradient boosting.

Advanced features for partial least squares (PLS) regression in the Fit Model platform. Model effects can include categorical factors, as well as crossed and polynomial terms.

Build cross-validated boosted decision-tree models, which build many simple trees, repeatedly fitting any residual variation from one tree to the next.

The bootstrap forest technique grows dozens of decision trees using random subsets of the available data and then averages the computed influence of each factor in these trees.

Stepwise regression includes the option of stopping rules based on cross-validation.

JMP Pro includes advanced computational methods for performing exact measures of association and oneway nonparametric exact tests.

Use Generalized Regression in JMP Pro to build better predictive models despite data challenges.

Compare the effect of different architectures on a neural fit with boosting (left) and without (right).

Partial least squares (PLS) regression can impute missing data before fitting.

Build and fit mixed models to analyze data that involves both time and space.

Model comparision provisions for comparing fits across multiple fit predictions.

Build multi-layer, cross-validated neural network models with numerous architectures.

Bootstrap any statistic in a JMP report with a single click. This example shows bootstrapping confidence limits around a 10th percentile quantile.

Use the Reliability Block Diagram for complex system design and to locate and address weaknesses in the system.

Uplift models identify the consumer segments most likely to respond favorably to an offer or treatment.

Easily split your data into training, validation and test portions for honest assessment of a model’s predictive ability.

Use variable clustering for quick and easy dimension reduction to make your prediction problems easier to solve.

Severity analysis of adverse events shows differences across treatment groups via dynamically linked graphs.

Tree maps like this one can show whether drug-event pairs meet signal criteria.

A simplified Starter menu helps users easily choose specific reports and analyses for dynamic visual exploration.

From one-way plots, select subjects of interest and drill down again to patient profiles.

This distribution shows duration of exposure for all subjects in the trial.

A Hierarchical Cluster report with two-way clustering identifies relationships between individual subjects and the events, findings and interventions included in the safety analyses for the study.

A two-dimensional hierarchical cluster shows relationships between selected events, findings or observations.

Zoom in to select subjects in the Hy’s Law region. Drill down on selected subjects to see patient profiles or subject clusters.

The default view for the JMP Clinical bubble plot is a representation of Hy’s Law analysis, showing changes across treatment groups over time for any lab.

The industry-standard Hy’s Law display in JMP Clinical is interactive for selection of subjects. A dashboard containing a scatterplot matrix of transaminases and bilirubin; mosaic plot of days until bilirubin elevation and missing lab tests report tab.

The mapping feature in Graph Builder lets you choose any variable for geographic display.

A new medical monitors dashboard in JMP Clinical 4 displays frequency and count information for adverse events.

Use Graph Builder’s Mosaic Plot to compare adverse events, here from the vascular body system, by sex across treatment groups.

Use the zoom tool in JMP Clinical to magnify clusters of interest, and then run a partial correlation analysis on any items in the cluster.

A patient profile dashboard allowing configuration of clinical information, notes for reviewers and printing to PDF documents.

Easily display the relative risk of significant adverse events.

In this bubble plot, time windows show the change in significance and relative risk for all adverse events and concomitant medications for each day of the trial.

From the volcano plot, drill down to a relative risk plot to sort easily by count, relative risk, significance or dictionary-derived terms.

From the severity analysis, select significant adverse events and drill down to the subject level with one-way plots.

A trellis plot graphs trends for selected subjects of interest.

From the volcano plot, a Venn diagram helps identify co-occurring adverse events for subjects in the study. Then select subjects for clustering or profiling.

Use paired RNA expression and DNA hybridization data to screen for indications of allele-specific expression with the new Allele Specific Expression Filter process. Examine a summary volcano plot, then drill down to display detailed information for specific SNPs.

Overlay continuous variables such as p-values, intensities, counts or fold changes on simple and complex genomes to identify interesting regions, then drill down to view detailed statistical results and tracks.

JMP Genomics 5 offers enhanced flexibility for movement of dendrograms and labels in cluster heat plots.

Significant enhancements to copy number partitioning let users display segment means, shade segments relative to a referencevalue, and filter results to display segmentsthat meet a pre-specified cutoff.

New segmentation summary plots can be filtered interactively to identify shared regions of copy number loss or gain.

Overlay continuous variables such as p-values, intensities, counts or fold changes on simple and complex genomes, with the option to display single chromosomes as circular. Identify interesting regions, then drill down to view detailed results and tracks.

Examine individual variations in copy number (left and upper right) or guide your search for shared regions with summary plots (lower right).

Create, compress, and incorporate genetic distance matrices into association tests that simultaneously correct for relatedness and population structure. Distance matrices may also be created to display relationships between continuous measures, or custom distance matrices clustered and visualized.

Analyze mRNA-seq data to find interesting patterns of differential expression with interactive volcano plot.

The customizable JMP Genomics Starter window, new in version 5, makes it easy for new and existing users to access tools appropriate to their analysis areas.

Scale count data across samples using TMM normalization, compare TMM factors between samples, and view kernel density plots of normalized data.

Visualize linkage maps created in JMP Genomics or imported from other software.

View p-values from statistical tests individually by chromosome, or create custom, multichromosome views.

Identify genomic regions that contain marker genotypes shared identical by state between related or unrelated individuals.

View ROC curves and assess your predictive models using a variety of ROC statistics.

Screen for SNP pair interactions using flexible filters, and drill down to view plots that display the details of trait values and SNP genotypes.

Display summaries of your statistical analyses in genome context to identify interesting regions with pre-built settings for commonly used genomes, or by creating custom genome views. Then drill down to overlay gene, histogram, SNP and heat plot tracks on statistical results. Here, p-values across a genomic region are overlaid with co-localized genes and a histogram track that summarizes raw exon-level data for two samples of particular interest.

Interactive triangular plots let you calculate and visualize linkage disequilibrium measures, identify LD blocks and zoom into interesting regions.

See batch effects in your data and remove them prior to statistical analysis.

Visualize shared patterns with multiway Venn diagrams. Overlay statistical findingsand annotation categories to drill down on the most important gene sets.

Examine a summary volcano plot to identify pathways that are over- or under-represented in your significant gene list, using a variety of enrichment tests.

Create bar charts and other graphs for multiple X or Y variables.

A box plot and bar chart shown in edit mode. Multiple graphs can be displayed at the same time.

High-quality map regions are built into the app for visualizing geographic data.

Create outlier box plots, or select another box plot style.

Display contour plots and violin plots using the contour icon.

Customize the look and feel of your graphs. Change graph properties, colors, line widths, marker sizes and more.Display contour plots and violin plots using the contour icon.

Focus on specific parts of the data in your graph using a data filter.

Variables can be dragged and dropped to any of the drop zones to change parameters of the graph.

Fit a regression line, and add confidence intervals and prediction intervals.

Explore regression lines for categories of a grouping variable.

Drag one variable to the X or Y zone and use the histogram icon to create a histogram.

Add a Group X or Group Y variable to create separate graphs. Add a variety of available summary statistics.

Import JMP data tables from iTunes or Dropbox, or any website, or open JMP data from an e-mail attachment.

View the JMP data table.

Create line graphs (run charts) for multiple overlaid variables.

Fit a number of functions to data including linear, quadratic and cubic fits.

Graph builder includes online samples and resources to help you get started quickly.

Add summary statistics to your graphs.

Build multivariate scatterplots to visualize correlations between variables.

Share your results with others.

Fit a smoothing spline to data to explore the relationship between two variables.

Build stacked bar charts, or a variety of other bar chart styles, with or without summary statistics.

Zoom into the values of individual points using the magnifier by tapping and holding the screen.

Use the Wrap zone to display graphs when there are several categories of a grouping variable.