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

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

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

22 p.-6 fig.-3 tab.-1 fig. supl.-6 tab. supl.-1 graph. abst.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.This work was funded in part by the NASA Space Biology program within the NASA Science Mission Directorate's (SMD) Biological and Physical Sciences (BPS) Division, NASA award numbers NNX15AG56G, 80NSSC19K0132, the Biotechnology and Biological Sciences Research Council (grant number BB/N015894/1), the MRC Versus Arthritis Centre for Musculoskeletal Ageing Research (grant numbers MR/P021220/1 and MR/R502364/1), the Spanish Research Agency (AEI grant number RTI2018-099309-B-I00, co-funded by EU-ERDF), and the National Institute for Health Research Nottingham Biomedical Research Centre.Peer reviewe