DegNorm: Normalization of generalized transcript degradation improves accuracy in RNA-seq analysis

Bin Xiong, Yiben Yang, Frank R. Fineis, Ji Ping Wang*

*Corresponding author for this work

Research output: Contribution to journalReview article

Abstract

RNA degradation affects RNA-seq quality when profiling transcriptional activities in cells. Here, we show that transcript degradation is both gene- and sample-specific and is a common and significant factor that may bias the results in RNA-seq analysis. Most existing global normalization approaches are ineffective to correct for degradation bias. We propose a novel pipeline named DegNorm to adjust the read counts for transcript degradation heterogeneity on a gene-by-gene basis while simultaneously controlling for the sequencing depth. The robust and effective performance of this method is demonstrated in an extensive set of simulated and real RNA-seq data.

Original languageEnglish (US)
Article number75
JournalGenome biology
Volume20
Issue number1
DOIs
StatePublished - Apr 16 2019

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Keywords

  • Alternative splicing
  • Degradation normalization
  • Non-negative matrix factorization
  • Normalization
  • RNA degradation
  • RNA-seq

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology

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