NVT: a fast and simple tool for the assessment of RNA-seq normalization strategies
Author(s) -
Thomas Eder,
Florian Grebien,
Thomas Rattei
Publication year - 2016
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btw521
Subject(s) - normalization (sociology) , computer science , data mining , database normalization , visualization , r package , artificial intelligence , pattern recognition (psychology) , sociology , anthropology , computational science
Measuring differential gene expression is a common task in the analysis of RNA-Seq data. To identify differentially expressed genes between two samples, it is crucial to normalize the datasets. While multiple normalization methods are available, all of them are based on certain assumptions that may or may not be suitable for the type of data they are applied on. Researchers therefore need to select an adequate normalization strategy for each RNA-Seq experiment. This selection includes exploration of different normalization methods as well as their comparison. Methods that agree with each other most likely represent realistic assumptions under the particular experimental conditions.
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