PRAM: a novel pooling approach for discovering intergenic transcripts from large-scale RNA sequencing experiments.

ABSTRACT: Publicly available RNA-seq data is routinely used for retrospective analysis to elucidate new biology. Novel transcript discovery enabled by joint analysis of large collections of RNA-seq data sets has emerged as one such analysis. Current methods for transcript discovery rely on a '2-Step' approach where the first step encompasses building transcripts from individual data sets, followed by the second step that merges predicted transcripts across data sets. To increase the power of transcript discovery from large collections of RNA-seq data sets, we developed a novel '1-Step' approach named Pooling RNA-seq and Assembling Models (PRAM) that builds transcript models from pooled RNA-seq data sets. We demonstrate in a computational benchmark that 1-Step outperforms 2-Step approaches in predict

SUBMITTER: Liu P 

PROVIDER: S-EPMC7605252 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature