Genomics Inform.  2018 Dec;16(4):e36. 10.5808/GI.2018.16.4.e36.

COEX-Seq: Convert a Variety of Measurements of Gene Expression in RNA-Seq

Affiliations
  • 1Division of Bio-Medical Informatics, Center for Genome Science, National Institute of Health, Korea Centers for Disease Control and Prevention, Cheongju 28159, Korea. sckim.knih@korea.kr
  • 2Department of Statistics, Inha University, Incheon 22212, Korea.

Abstract

Next generation sequencing (NGS), a high-throughput DNA sequencing technology, is widely used for molecular biological studies. In NGS, RNA-sequencing (RNA-Seq), which is a short-read massively parallel sequencing, is a major quantitative transcriptome tool for different transcriptome studies. To utilize the RNA-Seq data, various quantification and analysis methods have been developed to solve specific research goals, including identification of differentially expressed genes and detection of novel transcripts. Because of the accumulation of RNA-Seq data in the public databases, there is a demand for integrative analysis. However, the available RNA-Seq data are stored in different formats such as read count, transcripts per million, and fragments per kilobase million. This hinders the integrative analysis of the RNA-Seq data. To solve this problem, we have developed a web-based application using Shiny, COEX-seq (Convert a Variety of Measurements of Gene Expression in RNA-Seq) that easily converts data in a variety of measurement formats of gene expression used in most bioinformatic tools for RNA-Seq. It provides a workflow that includes loading data set, selecting measurement formats of gene expression, and identifying gene names. COEX-seq is freely available for academic purposes and can be run on Windows, Mac OS, and Linux operating systems. Source code, sample data sets, and supplementary documentation are available as well.

Keyword

integrative analysis; measurements of gene expression; RNA-Seq; web-based application using Shiny

MeSH Terms

Computational Biology
Dataset
Gene Expression*
High-Throughput Nucleotide Sequencing
Transcriptome
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