Fiche du document
1 mai 2018
- doi: 10.1093/bioinformatics/btx835
- issn: 1367-4803
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1093/bioinformatics/btx835
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/pmid/29309527
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/eissn/1367-4811
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_11FF54BB96E10
info:eu-repo/semantics/openAccess , Copying allowed only for non-profit organizations , https://serval.unil.ch/disclaimer
Sujets proches
Analysis (Mathematics)Citer ce document
H.G. Drost et al., « myTAI: evolutionary transcriptomics with R. », Serveur académique Lausannois, ID : 10.1093/bioinformatics/btx835
Métriques
Partage / Export
Résumé
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.