aFold – using polynomial uncertainty modelling for differential gene expression estimation from RNA sequencing data

aFold – using polynomial uncertainty modelling for differential gene expression estimation from RNA sequencing data

Abstract Background Data normalization and identification of significant differential expression represent crucial steps in RNA-Seq analysis. Many available tools rely on assumptions that are often not met by real data, including the common assumption of symmetrical distribution of up- and down-regu...

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Bibliographic Details
Main Authors: Wentao Yang, Philip Rosenstiel, Hinrich Schulenburg
Format: Article
Language:English
Published: BMC 2019-05-01
Series:BMC Genomics
Subjects:
Differential expression analysis
RNASeq
Transcriptomics
Normalization
ABSSeq
DESeq2
Online Access:http://link.springer.com/article/10.1186/s12864-019-5686-1

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http://link.springer.com/article/10.1186/s12864-019-5686-1

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