myTAI: evolutionary transcriptomics with R.
Details
Download: btx835.pdf (81.23 [Ko])
State: Public
Version: Final published version
State: Public
Version: Final published version
Serval ID
serval:BIB_11FF54BB96E1
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
myTAI: evolutionary transcriptomics with R.
Journal
Bioinformatics
ISSN
1367-4811 (Electronic)
ISSN-L
1367-4803
Publication state
Published
Issued date
01/05/2018
Peer-reviewed
Oui
Volume
34
Number
9
Pages
1589-1590
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Publication Status: ppublish
Abstract
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.
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.
The open source myTAI package is available at https://github.com/HajkD/myTAI and https://cran.r-project.org/web/packages/myTAI/index.html.
hgd23@cam.ac.uk.
Supplementary data are available at Bioinformatics online.
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.
The open source myTAI package is available at https://github.com/HajkD/myTAI and https://cran.r-project.org/web/packages/myTAI/index.html.
hgd23@cam.ac.uk.
Supplementary data are available at Bioinformatics online.
Keywords
Biological Evolution, Genomics, Software, Transcriptome
Pubmed
Web of science
Open Access
Yes
Create date
12/04/2018 15:00
Last modification date
21/11/2022 8:19