Differential expression in RNA-seq: A matter of depth

• DOI: 10.1101/gr.124321.111
• Publication Date: 2011-09-09T13:01:50Z
• Authors: Sonia Tarazona; Fernando García-A...; Joaquín Dopazo; Alberto Ferrer; Ana Conesa
• Keywords: RNA-Seq; Single cell sequencing

Next-generation sequencing (NGS) technologies are revolutionizing genome research, and in particular, their application to transcriptomics (RNA-seq) is increasingly being used for gene expression profiling as a replacement microarrays. However, the properties of RNA-seq data have not been yet fully established, additional research needed understanding how these respond differential analysis. In this work, we set out gain insights into characteristics analysis by studying an important parameter technology: depth. We analyzed depth affects detection transcripts identification differentially expressed, looking at aspects such transcript biotype, length, level, fold-change. evaluated different algorithms available proposed novel approach—NOISeq—that differs from existing methods that it data-adaptive nonparametric. Our results reveal most methodologies suffer strong dependency on calls considerable number false positives increases reads grows. contrast, our method models noise distribution actual data, can therefore better adapt size set, more effective controlling rate discoveries. This work discusses true potential regulation low ranges, within issue replication.