While many data scientists use resources listed on New User and Intermediate User pages to effectively use IPA for core analyses, they are often working with high volumes of different omics data (example RNA-seq, proteomics etc.) and are therefore interested in more advanced capabilities such as batch loading and analyzing datasets, setting up comparisons, incorporating public data and more.
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Using the IPA user interface (for API access see “APIs” section below)
Some data analysts are interested in importing pathways into IPA from other sources such as Cytoscape.
Many data scientists are interested in uploading datasets and setting up analyses in IPA programmatically via python or R. Others are interested in use cases such as displaying information about their drug target, biomarker, or gene of interest from IPA’s comprehensive knowledge base, or for example sending genes to IPA to automatically generate a network.
Data scientists have shown interest in directly using the knowledge base and knowledge graph that underpins QIAGEN Ingenuity Pathway Analysis. If interested, please visit this page:
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