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myTAI: evolutionary transcriptomics with R

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 bio...

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Detalles Bibliográficos
Autores principales: Drost, Hajk-Georg, Gabel, Alexander, Liu, Jialin, Quint, Marcel, Grosse, Ivo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5925770/
https://www.ncbi.nlm.nih.gov/pubmed/29309527
http://dx.doi.org/10.1093/bioinformatics/btx835
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.