To join or not to join: handling biological replicates in long-read RNA sequencing data.

ABSTRACT: Long-read RNA sequencing (lrRNA-seq) has revolutionized transcriptomics facilitating the study of alternative splicing and resulting in identification of thousands of novel transcripts. While isoform identification has received significant attention, the handling of biologically replicated lrRNA-seq datasets remains less explored. However, how multiple samples are combined in a lrRNA-seq study may strongly impact transcript identification. This study defines and evaluates two strategies for obtaining consensus transcriptomes from multi-sample lrRNA-seq data: "Join & Call", where reads from all samples are combined before transcript identification, and "Call & Join", where transcript identification is performed on individual samples before combining the resulting annotations. We applied the

SUBMITTER: Jetzinger F 

PROVIDER: S-EPMC12715542 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature