GenomicSuperSignature facilitates interpretation of RNA-seq experiments through robust, efficient comparison to public databases.

ABSTRACT: Millions of transcriptomic profiles have been deposited in public archives, yet remain underused for the interpretation of new experiments. We present a method for interpreting new transcriptomic datasets through instant comparison to public datasets without high-performance computing requirements. We apply Principal Component Analysis on 536 studies comprising 44,890 human RNA sequencing profiles and aggregate sufficiently similar loading vectors to form Replicable Axes of Variation (RAV). RAVs are annotated with metadata of originating studies and by gene set enrichment analysis. Functionality to associate new datasets with RAVs, extract interpretable annotations, and provide intuitive visualization are implemented as the GenomicSuperSignature R/Bioconductor package. We demonstrate the e

SUBMITTER: Oh S 

PROVIDER: S-EPMC9237024 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature