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Analyzing large transcriptomics or proteomics datasets typically involves answering two broad questions regarding the set of differentially-expressed genes or proteins

Analyzing large transcriptomics or proteomics datasets typically involves answering two broad questions regarding the set of differentially-expressed genes or proteins:

1. What does the data reveal about the underlying biology in the sampled cells or tissues
2. What relevance does that biological information have with respect to other biological samples? We want to understand whether the phenomenon is unusual or commonplace, and whether there are informative similarities to other areas of biology.

This white paper describes how Ingenuity Pathway Analysis (IPA) was created to answer the first question and Analysis Match was created within IPA to answer the second.

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