biostudies-literatureUrzua-Traslavina CGEuropean Research CouncilDutch Research Council (NWO)1464https://www.ebi.ac.uk/biostudies/studies/S-EPMC7935959biostudies-literatureUnknown12(1)The interpretation of high throughput sequencing data is limited by our incomplete functional understanding of coding and non-coding transcripts. Reliably predicting the function of such transcripts can overcome this limitation. Here we report the use of a consensus independent component analysis and guilt-by-association approach to predict over 23,000 functional groups comprised of over 55,000 coding and non-coding transcripts using publicly available transcriptomic profiles. We show that, compared to using Principal Component Analysis, Independent Component Analysis-derived transcriptional components enable more confident functionality predictions, improve predictions when new members are added to the gene sets, and are less affected by gene multi-functionality. Predictions generated usiNature communicationsImproving gene function predictions using independent transcriptional components.PMC793595968242116025Leeuwenburgh VCde Vries EGEBhattacharya AFehrmann RSNLoipfinger SUrzua-Traslavina CGvan Vugt MATMfalseImproving gene function predictions using independent transcriptional components.The interpretation of high throughput sequencing data is limited by our incomplete functional understanding of coding and non-coding transcripts. Reliably predicting the function of such transcripts can overcome this limitation. Here we report the use of a consensus independent component analysis and guilt-by-association approach to predict over 23,000 functional groups comprised of over 55,000 coding and non-coding transcripts using publicly available transcriptomic profiles. We show that, compared to using Principal Component Analysis, Independent Component Analysis-derived transcriptional components enable more confident functionality predictions, improve predictions when new members are added to the gene sets, and are less affected by gene multi-functionality. Predictions generated usi2021-01-01T00:00:00Z2021 Mar2025-04-22T02:06:10.962Z2025-04-05T20:14:53.29ZS-EPMC79359593367461010.1038/s41467-021-21671-w