Running this process using the DrosophilaAgingExample sample setting generates the tabbed Results window shown below. Refer to the One-Way ANOVA process description for more information. Output from the process is organized into tabs. Each tab contains one or more plots, data panels, data filters, and so on. that facilitate your analysis.
The Results window contains the following panes:
Tabs
This pane enables you to access and view the output plots and associated data sets on each tab. Use the drop-down menu to view the tab in the Tab Viewer pane, open the tab in a new window, or remove the tab and its contents from the Tab Viewer pane.
The following tabs are generated by this process:
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Results: This tab shows the primary results from the analysis, including volcano plots and various analyses on least squares means
SAS Output: This is a text-based output directly from SAS PROC UNIVARIATE. Refer to the documentation for SAS PROC UNIVARIATE for more information.
Drill Downs
Action buttons provide you with an easy way to drill down into your data.
The following action buttons are generated by this process:
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IPA Upload: Select points or rows and click to open the IPA Upload process with the selected points specified as input data.
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UCSC Genome Browser: Select points or rows and click to open the UCSC Genome Browser process with the selected points specified as input data.
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Annotation Summary: Select points or rows and click to summarize annotation information for the selected genes or markers
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GO Stat: Select points or rows and click to access, annotate, and analyze information for selected molecular entities in the Gene Ontology database.
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Onto-Express: Select points or rows and click to retrieve annotation information for selected gene or markers from the Onto-Express database
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GenBank Nucleotide: Select points or rows and click to opens a browser window directed to a GenBank Nucleotide search for the selected molecular entities.
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UniGene Database: Select points or rows and click to open a browser window directed to a UniGene Database search for the selected molecular entities.
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AceView Database: Select points or rows and click to access information from the ACEView database for selected genes or markers.
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Open Subset in Tall Format: Select points or rows and click to create a tall version of the input data for the selected genes.
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Open Subset in Wide Format: Select points or rows and click to create a wide version of the input data for the selected genes.
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Fit Model and Plot LS Means: Select points or rows and click to select variable(s) that uniquely define wide column names. Selected genes are analyzed in the JMP Fit Model platform to view detailed fitting results and plots.
Attention: Read the warning found in the link.
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Construct One-way Plots: Click to plot the original data in one-way format using treatment variables of your choice.
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Launch Plot Intensities: Select points or rows and click to launch the Plot Intensities process on the selected genes.
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Venn Diagram: Click to launch an open dialog from which you can select up to 5 comparisons and create a Venn diagram to display the overlap of significant genes from those comparisons.
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Launch JMP Genomics Browser: Select points or rows and click to launch the JMP Genomics Browser process for the selected points.
Enter new -log10(p) cutoff: Enter a new value in the text box to change the horizontal dashed red line in the volcano plots that is used for determining statistical significance. Click to update all plots to reflect the new cutoff.
Output Data
This process generates the following data set:
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Significant Differences Data Set: This output data set contains a complete list of the genes significant by one or more criteria. This data set is indicated by the _sig suffix. Click to view the data set.
For detailed information about the files and data sets used or created by JMP Genomics software, see Files and Data Sets.
Tab Viewer
This pane provides you with a space to view individual tabs within the Results window.
General
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Click to surface the data sets corresponding to the active tab.
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Click to reopen the completed process dialog used to generate this output.
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Click to generate a pdf- or rtf-formatted report containing the plots and charts of selected tabs.
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Click to close all graphics windows and underlying data sets associated with the output.
Additional Information About this Analysis
Both ANOVA and One-Way ANOVA in JMP G use standard linear mixed model approaches based on normal theory to calculate the resulting t-and F-tests. When differences occur with results from other software packages, the typical place to look is in the degrees of freedom approximation used behind the t-and F-tests. Different approximations for these are possible and there is not necessarily one best answer, especially if there are missing data. If you want to break things down further, consider the numerator and denominator of a specific single-degree-of-freedom t-test for a few select genes to really get to the bottom of it.
One suggestion for assessing the results of these processes is transforming the p-values to -log10 scale and plotting them versus each other. They should be highly correlated although not perfectly so, providing basically the same ordering of the genes. If they are radically different, something may be off in the model setup itself in terms of the factors specified. Contact JMP Tech support for help in deciphering exactly what is going on in your situation.
One Way ANOVA in JMPG performs its calculations directly in a SAS data step for speed, although it is limited to one-way designs with one blocking factor. Note though that multi-way designs can be converted to one-way by creating a single super factor that has all possible levels. ANOVA in JMPG calls SAS PROC MIXED with BY groups.
You can also use the -log2fold change itself (numerator of t-statistic) to sort genes for reproducibility. Those with larger fold changes are typically more reproducible. In volcano plots, look for genes in the upper left and right corners.
