Covering all your bases: incorporating intron signal from RNA-seq data
Stuart Lee, Albert Y Zhang, Shian Su, Ashley P Ng, Aliaksei Z Holik, Marie-Liesse Asselin-Labat, Matthew E Ritchie, Charity W Law
NAR GENOMICS AND BIOINFORMATICS | OXFORD UNIV PRESS | Published : 2020
RNA-seq datasets can contain millions of intron reads per library that are typically removed from downstream analysis. Only reads overlapping annotated exons are considered to be informative since mature mRNA is assumed to be the major component sequenced, especially for poly(A) RNA libraries. In this study, we show that intron reads are informative, and through exploratory data analysis of read coverage that intron signal is representative of both pre-mRNAs and intron retention. We demonstrate how intron reads can be utilized in differential expression analysis using our index method where a unique set of differentially expressed genes can be detected using intron counts. In exploring read ..View full abstract
Awarded by National Health and Medical Research Council (NHMRC) Fellowship
Awarded by NHMRC
National Health and Medical Research Council (NHMRC) Fellowship [GNT1104924 to M.E.R.]; NHMRC Project grants [GNT1098290, GNT1124812, GNT1138275, GNT1140976, GNT1143163 to M.E.R., GNT1060179 to A.P.N.]; Victorian State Government Operational Infrastructure Support; NHMRC Independent Research Institute Infrastructure Support Scheme (IRIISS).