TEffectR: an R package for studying the potential effects of transposable elements on gene expression with linear regression model.
Gene expression
Linear model
R package
Regression
Gene regulation
Transposable elements
Journal
PeerJ
ISSN: 2167-8359
Titre abrégé: PeerJ
Pays: United States
ID NLM: 101603425
Informations de publication
Date de publication:
2019
2019
Historique:
received:
15
08
2019
accepted:
11
11
2019
entrez:
12
12
2019
pubmed:
12
12
2019
medline:
12
12
2019
Statut:
epublish
Résumé
Recent studies highlight the crucial regulatory roles of transposable elements (TEs) on proximal gene expression in distinct biological contexts such as disease and development. However, computational tools extracting potential TE -proximal gene expression associations from RNA-sequencing data are still missing. Herein, we developed a novel R package, using a linear regression model, for studying the potential influence of TE species on proximal gene expression from a given RNA-sequencing data set. Our R package, namely TEffectR, makes use of publicly available RepeatMasker TE and Ensembl gene annotations as well as several functions of other R-packages. It calculates total read counts of TEs from sorted and indexed genome aligned BAM files provided by the user, and determines statistically significant relations between TE expression and the transcription of nearby genes under diverse biological conditions. TEffectR is freely available at https://github.com/karakulahg/TEffectR along with a handy tutorial as exemplified by the analysis of RNA-sequencing data including normal and tumour tissue specimens obtained from breast cancer patients.
Identifiants
pubmed: 31824778
doi: 10.7717/peerj.8192
pii: 8192
pmc: PMC6899341
doi:
Types de publication
Journal Article
Langues
eng
Pagination
e8192Informations de copyright
©2019 Karakülah et al.
Déclaration de conflit d'intérêts
Gökhan Karakülah and Aslı Suner are Academic Editors for PeerJ.
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