Data quality aware analysis of differential expression in RNA-seq with NOISeq R/Bioc package

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ID: 305219
2015
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Abstract
As the use of RNA-seq has popularized, there is an increasing consciousness of the importance of experimental design, bias removal, accurate quantification and control of false positives for proper data analysis. We introduce the NOISeq R-package for quality control and analysis of count data. We show how the available diagnostic tools can be used to monitor quality issues, make pre-processing decisions and improve analysis. We demonstrate that the non-parametric NOISeqBIO efficiently controls false discoveries in experiments with biological replication and outperforms state-of-the-art methods. NOISeq is a comprehensive resource that meets current needs for robust data-aware analysis of RNA-seq differential expression.
Reference Key
openalex_W2127274965 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Sonia Tarazona, Pedro Furió‐Tarí, David Turrà, Antonio Di Pietro, María José Nueda, Alberto Ferrer, Ana Conesa
Journal Nucleic Acids Research
Year 2015
DOI
10.1093/nar/gkv711
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