myTAI: Evolutionary transcriptomics with R

Hajk-Georg Drost (Lead / Corresponding author), Alexander Gabel, Jialin Liu, Marcel Quint, Ivo Grosse

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)

Abstract

Motivation Next Generation Sequencing (NGS) technologies generate a large amount of high quality transcriptome datasets enabling the investigation of molecular processes on a genomic and metagenomic scale. These transcriptomics studies aim to quantify and compare the molecular phenotypes of the biological processes at hand. Despite the vast increase of available transcriptome datasets, little is known about the evolutionary conservation of those characterized transcriptomes. Results The myTAI package implements exploratory analysis functions to infer transcriptome conservation patterns in any transcriptome dataset. Comprehensive documentation of myTAI functions and tutorial vignettes provide step-by-step instructions on how to use the package in an exploratory and computationally reproducible manner. Availability and implementation The open source myTAI package is available at https://github.com/HajkD/myTAI and https://cran.r-project.org/web/packages/myTAI/index.html. Contact [email protected] Supplementary informationSupplementary dataare available at Bioinformatics online.

Original languageEnglish
Pages (from-to)1589-1590
Number of pages2
JournalBioinformatics
Volume34
Issue number9
Early online date22 Dec 2017
DOIs
Publication statusPublished - May 2018

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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