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NASA GeneLab RNA-seq consensus pipeline: Standardized processing of short-read RNA-seq data

Authors :
Eliah G. Overbey
Amanda M. Saravia-Butler
Zhe Zhang
Komal S. Rathi
Homer Fogle
Willian A. da Silveira
Richard J. Barker
Joseph J. Bass
Afshin Beheshti
Daniel C. Berrios
Elizabeth A. Blaber
Egle Cekanaviciute
Helio A. Costa
Laurence B. Davin
Kathleen M. Fisch
Samrawit G. Gebre
Matthew Geniza
Rachel Gilbert
Simon Gilroy
Gary Hardiman
Raúl Herranz
Yared H. Kidane
Colin P.S. Kruse
Michael D. Lee
Ted Liefeld
Norman G. Lewis
J. Tyson McDonald
Robert Meller
Tejaswini Mishra
Imara Y. Perera
Shayoni Ray
Sigrid S. Reinsch
Sara Brin Rosenthal
Michael Strong
Nathaniel J. Szewczyk
Candice G.T. Tahimic
Deanne M. Taylor
Joshua P. Vandenbrink
Alicia Villacampa
Silvio Weging
Chris Wolverton
Sarah E. Wyatt
Luis Zea
Sylvain V. Costes
Jonathan M. Galazka
Source :
iScience, Vol 24, Iss 4, Pp 102361- (2021)
Publication Year :
2021
Publisher :
Elsevier, 2021.

Abstract

Summary: With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility, and reusability of pipeline data; to provide a template for data processing of future spaceflight-relevant datasets; and to encourage cross-analysis of data from other databases with the data available in GeneLab.

Subjects

Subjects :
Omics
Space Sciences
Science

Details

Language :
English
ISSN :
25890042
Volume :
24
Issue :
4
Database :
Directory of Open Access Journals
Journal :
iScience
Publication Type :
Academic Journal
Accession number :
edsdoj.b05f4c13f9d4050b634492f121e3d68
Document Type :
article
Full Text :
https://doi.org/10.1016/j.isci.2021.102361