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Genome Biol ; 20(1): 75, 2019 04 16.
Article in English | MEDLINE | ID: mdl-30992037

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.


Subject(s)
Algorithms , RNA Stability , Sequence Analysis, RNA , Cell Line , Humans , Software
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