Normalization of generalized transcript degradation improves accuracy in RNA-seq analysis
RNA-seq is a high-throughput assay to profile transcriptional activities in cells. Here we show that transcript degradation is gene-/sample-specific and presents a common and major source that may substantially bias the results in RNA-seq analysis. Most existing global normalization approaches are ineffective to correct for the degradation bias. We propose a novel pipeline named DegNorm (stands for degradation normalization) to adjust read counts for transcript degradation heterogeneity on a gene-by-gene basis while simultaneously controlling the sequencing depth. The robust and effective performance of this method is demonstrated in an extensive set of real RNA-seq data and simulated data.
bioinformatics↗