JMP Genomics Starter

JMP Genomics Starter
Click on a category to reveal subcategories and processes. Refer to the table below for guidance.
Adding, managing, renaming, combining, and deleting studies. A study is a construct that helps you organize and track the data sets and settings associated with a particular study or project. See the Studies page for more information.
All data sets of the same type (for example, wide) per study must be found in the same folder.
Running and building workflows. A workflow is a sequence of processes to run in a specific order -- an analytical pipeline. Once built, a workflow can be repeatedly called, eliminating the need to repeatedly set parameters for each of the individual processes. See the Workflows page for more information.
Tall or wide Input Data Sets, Experimental Design Data Set (EDDS)s, and/or Annotation Data Sets, depending on the underlying processes.
Quality assessment, normalization, modeling, manipulation, and submission of expression data.
Tip: Explore data quality and evaluate the need for normalization before using these processes.
Construction of continuous or categorical outcome predictors using data from genetic markers, microarrays, or proteomics as predictor variables. Model comparison and data preparation utilities are also available.
Viewing, adjusting, and combining p-values in preparation for more detailed analyses.

Following the import of data (an Experimental Design File (EDF) is sometimes required), Tall and Wide Data Sets (which are SAS Data Sets) are the most common primary Input Data Sets required throughout JMP Genomics. Less common are stacked, square, and other specialized varieties. (See Other Types of Data Sets.) In many cases, an additional Experimental Design Data Set (EDDS), Annotation Data Set, or settings file is either specifiable or required. See Data Sets Used in JMP Genomics Processes and the documentation for individual processes for additional information.