4.7 Article

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

Journal

ISCIENCE
Volume 24, Issue 4, Pages -

Publisher

CELL PRESS
DOI: 10.1016/j.isci.2021.102361

Keywords

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Funding

  1. NASA Space Biology program within the NASA Science Mission Directorate's (SMD) Biological and Physical Sciences (BPS) Division, NASA [NNX15AG56G, 80NSSC19K0132]
  2. Biotechnology and Biological Sciences Research Council [BB/N015894/1]
  3. MRC Versus Arthritis Centre for Musculoskeletal Ageing Research [MR/P021220/1, MR/R502364/1]
  4. Spanish Research Agency (AEI) [RTI2018-099309-B-I00]
  5. EU-ERDF
  6. National Institute for Health Research Nottingham Biomedical Research Centre
  7. NASA [804910, NNX15AG56G] Funding Source: Federal RePORTER

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With the advancement of transcriptomic technologies, NASA GeneLab and associated working groups have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight experiments, which is now publicly available. This aims to promote transparency, reproducibility, and reusability of data, provide a template for future data processing, and encourage cross-analysis of data from different databases.
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.

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