NASA GeneLab RNA-seq consensus pipeline: standardized processing of short-read RNA-seq data.
NASA GeneLab RNA-seq consensus pipeline: standardized processing of short-read RNA-seq data.
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DOI：
10.1016/j.isci.2021.102361
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发表时间：
2021-04-23
期刊：
影响因子：
5.8
通讯作者：
Galazka JM
中科院分区：
文献类型：
--
作者：
Overbey EG;Saravia-Butler AM;Zhang Z;Rathi KS;Fogle H;da Silveira WA;Barker RJ;Bass JJ;Beheshti A;Berrios DC;Blaber EA;Cekanaviciute E;Costa HA;Davin LB;Fisch KM;Gebre SG;Geniza M;Gilbert R;Gilroy S;Hardiman G;Herranz R;Kidane YH;Kruse CPS;Lee MD;Liefeld T;Lewis NG;McDonald JT;Meller R;Mishra T;Perera IY;Ray S;Reinsch SS;Rosenthal SB;Strong M;Szewczyk NJ;Tahimic CGT;Taylor DM;Vandenbrink JP;Villacampa A;Weging S;Wolverton C;Wyatt SE;Zea L;Costes SV;Galazka JM
随着转录组学技术的发展，我们能够量化宇航员和其他暴露于太空飞行的生物体的基因表达谱的精确变化。美国宇航局基因实验室和基因实验室相关分析工作组（AWG）的成员开发了一个共识管道，用于分析来自太空飞行相关实验的短读RNA测序数据。该流程包括质量控制、读段修剪、映射和基因定量步骤，最终检测差异表达的基因。该数据分析管道及其使用提交给GeneLab的数据执行的结果现在都可以通过GeneLab数据库公开获得。我们在此介绍了构建该管道的完整细节和原理，以提高管道数据的透明度、可重复性和可重用性;为未来航天相关数据集的数据处理提供模板;并鼓励交叉分析来自其他数据库的数据与GeneLab中可用的数据。分析来自不同航天研究的组学数据提出了独特的挑战RNA-seq分析的标准化管道消除了数据处理的差异GeneLab RNA-seq管道包括QC、修剪、绘图、定量和DGE。genelab.nasa.gov
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. Analysis of omics data from different spaceflight studies presents unique challenges A standardized pipeline for RNA-seq analysis eliminates data processing variation The GeneLab RNA-seq pipeline includes QC, trimming, mapping, quantification, and DGE Space-relevant data processed with this pipeline are available at genelab.nasa.gov Omics; Space Sciences
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影响因子：
48
作者：
Huber W;Carey VJ;Gentleman R;Anders S;Carlson M;Carvalho BS;Bravo HC;Davis S;Gatto L;Girke T;Gottardo R;Hahne F;Hansen KD;Irizarry RA;Lawrence M;Love MI;MacDonald J;Obenchain V;Oleś AK;Pagès H;Reyes A;Shannon P;Smyth GK;Tenenbaum D;Waldron L;Morgan M
通讯作者：
Morgan M
DOI：
10.1016/j.patter.2020.100148
发表时间：
2020-12-11
期刊：
Patterns (New York, N.Y.)
影响因子：
--
作者：
Rutter L;Barker R;Bezdan D;Cope H;Costes SV;Degoricija L;Fisch KM;Gabitto MI;Gebre S;Giacomello S;Gilroy S;Green SJ;Mason CE;Reinsch SS;Szewczyk NJ;Taylor DM;Galazka JM;Herranz R;Muratani M
通讯作者：
Muratani M
影响因子：
12.3
作者：
Gentleman RC;Carey VJ;Bates DM;Bolstad B;Dettling M;Dudoit S;Ellis B;Gautier L;Ge Y;Gentry J;Hornik K;Hothorn T;Huber W;Iacus S;Irizarry R;Leisch F;Li C;Maechler M;Rossini AJ;Sawitzki G;Smith C;Smyth G;Tierney L;Yang JY;Zhang J
通讯作者：
Zhang J
影响因子：
46.9
作者：
Risso, Davide;Ngai, John;Speed, Terence P.;Dudoit, Sandrine
通讯作者：
Dudoit, Sandrine
影响因子：
3
作者：
Risso D;Schwartz K;Sherlock G;Dudoit S
通讯作者：
Dudoit S