The seeker R package: simplified fetching and processing of transcriptome data.

Autor:	Schoenbachler JL; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States., Hughey JJ; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.; Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States.
Jazyk:	angličtina
Zdroj:	PeerJ [PeerJ] 2022 Nov 07; Vol. 10, pp. e14372. Date of Electronic Publication: 2022 Nov 07 (Print Publication: 2022).
DOI:	10.7717/peerj.14372
Abstrakt:	Transcriptome data have become invaluable for interrogating biological systems. Preparing a transcriptome dataset for analysis, particularly an RNA-seq dataset, entails multiple steps and software programs, each with its own command-line interface (CLI). Although these CLIs are powerful, they often require shell scripting for automation and parallelization, which can have a high learning curve, especially when the details of the CLIs vary from one tool to another. However, many individuals working with transcriptome data are already familiar with R due to the plethora and popularity of R-based tools for analyzing biological data. Thus, we developed an R package called seeker for simplified fetching and processing of RNA-seq and microarray data. Seeker is a wrapper around various existing tools, and provides a standard interface, simple parallelization, and detailed logging. Seeker's primary output-sample metadata and gene expression values based on Entrez or Ensembl Gene IDs-can be directly plugged into a differential expression analysis. To maximize reproducibility, seeker is available as a standalone R package and in a Docker image that includes all dependencies, both of which are accessible at https://seeker.hugheylab.org. Competing Interests: Jacob J. Hughey is an Academic Editor for PeerJ. (© 2022 Schoenbachler and Hughey.)
Databáze:	MEDLINE
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