RNA-Seq offers significant advantages over existing high throughput methods for gene expression analysis, including far more precise measurement of levels of transcripts, ability to distinguish different isoforms, and a broader dynamic range to quantify gene expression levels. It is precisely these advantages, however, that make interpretation of RNA-Seq data a daunting task. The need for a better way to accurately interpret and distill such large amounts of data has never been more acute.
Ingenuity’s IPA applications enable you to upload, analyze, and visualize RNA-Seq datasets, eliminating the obstacles between data and biological insight, and helping to standardize RNA-Seq data analysis and interpretation. Insights gleaned from IPA of RNA-Seq data demonstrate a greatly improved workflow for bench scientists to proficiently handle RNA-Seq data and generate testable hypotheses.
With IPA support of RNA-Seq data, bench scientists are now able to quickly move forward to identify differentially expressed isoforms between condition and control samples, and interpret the impact of expression changes in the context of biological processes, disease and cellular phenotypes, and molecular interactions. With IPA you can:
- Easily narrow in on genes in your RNA-Seq samples that have multiple differentially expressed isoforms
- Visualize your RNA-Seq data in the context of Isoform View, which displays alternatively spliced transcripts and details of their chromosomal locus, predicted protein domains, and encoded protein isoforms
- Compile targeted bibliographies with experimental evidence linking your differentially expressed isoforms to biological processes, diseases, and molecular interactions
Click below for resources that describe IPA RNA-Seq analysis in more detail.