Introduction

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.

Publications

  1. Data quality aware analysis of differential expression in RNA-seq with NOISeq R/Bioc package.
    Cite this
    Tarazona S, Furió-Tarí P, Turrà D, Pietro AD, Nueda MJ, Ferrer A, Conesa A, 2015-12-01 - Nucleic acids research

Credits

  1. Sonia Tarazona
    Developer

    Genomics of Gene Expression Lab, Centro de Investigación Príncipe Felipe, United States of America

  2. Pedro Furió-Tarí
    Developer

    Genomics of Gene Expression Lab, Centro de Investigación Príncipe Felipe, United States of America

  3. David Turrà
    Developer

    Department of Genetics, Universidad de Córdoba, Spain

  4. Antonio Di Pietro
    Developer

    Department of Genetics, Universidad de Córdoba, Spain

  5. María José Nueda
    Developer

    Statistics and Operational Research Department, Universidad de Alicante, Spain

  6. Alberto Ferrer
    Developer

    Department of Applied Statistics, Operations Research and Quality, Spain

  7. Ana Conesa
    Investigator

    Genomics of Gene Expression Lab, Centro de Investigación Príncipe Felipe, United States of America

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Summary
AccessionBT000059
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Country/RegionSpain
Submitted ByAna Conesa