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Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
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Published on: September 18, 2021

TCC: an R package for comparing tag count data with robust normalization strategies.

Jianqiang Sun1, Tomoaki Nishiyama, Kentaro Shimizu

  • 1Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan.

BMC Bioinformatics
|July 11, 2013
PubMed
Summary

The TCC R package introduces a novel normalization strategy, DEG elimination strategy (DEGES), for RNA-seq data, significantly improving differential gene expression analysis accuracy and speed. This method is crucial for handling biased gene expression counts in biological samples.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • RNA sequencing (RNA-seq) is fundamental for studying gene expression.
  • Existing R packages for differential expression analysis lack multi-step normalization strategies.
  • The previously developed TbT normalization method is computationally intensive.

Purpose of the Study:

  • To develop a faster and more accurate normalization method for RNA-seq data.
  • To introduce the Tag Count Comparison (TCC) R package for differential gene expression analysis.
  • To implement a novel DEG elimination strategy (DEGES) for improved normalization.

Main Methods:

  • Developed the TCC R package incorporating multi-step normalization methods.
  • Implemented the DEG elimination strategy (DEGES) to remove potential differentially expressed genes (DEGs) before normalization.
  • Integrated functions from existing R packages (edgeR, DESeq, baySeq) for flexible analysis.

Main Results:

  • The TCC package provides faster normalization methods compared to the original TbT method.
  • DEGES normalization is essential for accurate analysis, especially with biased DEG counts.
  • TCC supports two-group and multi-group comparisons with or without replicates.

Conclusions:

  • The DEGES strategy in TCC is crucial for accurate tag count data normalization.
  • TCC is effective for analyzing RNA-seq data across various scenarios, including those with extreme DEG biases.
  • TCC offers a unified interface for differential expression analysis and is available via http://www.iu.a.u-tokyo.ac.jp/~kadota/TCC/ and Bioconductor.