Abstract
Alternative splicing and alternative transcription are a major mechanism for generating transcriptome diversity. Differential alternative splicing and transcription (DAST), which describe different usage of transcript isoforms across different conditions, can complement differential expression in characterizing gene regulation. However, the analysis of DAST is challenging because only a small fraction of RNA-seq reads is informative for isoforms. Several methods have been developed to detect exon-based and gene-based DAST, but they suffer from power loss for genes with many isoforms. We present PennDiff, a novel statistical method that makes use of information on gene structures and pre-estimated isoform relative abundances, to detect DAST from RNA-seq data. PennDiff has several advantages. First, grouping exons avoids multiple testing for 'exons' originated from the same isoform(s). Second, it utilizes all available reads in exon-inclusion level estimation, which is different from methods that only use junction reads. Third, collapsing isoforms sharing the same alternative exons reduces the impact of isoform expression estimation uncertainty. PennDiff is able to detect DAST at both exon and gene levels, thus offering more flex...Continue Reading
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