SPEAQeasy: a scalable pipeline for expression analysis and quantification for R/bioconductor-powered RNA-seq analyses.
SPEAQeasy: a scalable pipeline for expression analysis and quantification for R/bioconductor-powered RNA-seq analyses.
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DOI：
10.1186/s12859-021-04142-3
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发表时间：
2021-05-01
影响因子：
3
通讯作者：
Collado-Torres L
中科院分区：
文献类型：
--
作者：
Eagles NJ;Burke EE;Leonard J;Barry BK;Stolz JM;Huuki L;Phan BN;Serrato VL;Gutiérrez-Millán E;Aguilar-Ordoñez I;Jaffe AE;Collado-Torres L
RNA测序（RNA-seq）是一种常见和广泛的生物测定方法，并由此产生越来越多的数据。在实践中，在原始RNA-seq读取直接产生有价值的信息（如差异基因表达数据）之前，研究人员必须执行大量的单独步骤。现有的软件工具通常是专门化的，只执行一个步骤——比如将读取的数据与参考基因组进行比对——一个更大的工作流。对更全面和可重复的工作流程的需求导致了许多公开可用的RNA-seq管道的产生。然而，我们发现大多数需要计算专业知识来设置或在几个用户之间共享，没有积极维护，或者缺乏我们在自己的分析中发现的重要特性。为了解决这些问题，我们开发了一种可扩展的表达分析和定量管道（SPEAQeasy），它易于安装和共享，并为R/Bioconductor下游分析解决方案提供了桥梁。SPEAQeasy是可移植的计算框架（SGE， SLURM，本地，docker集成）和不同的配置文件提供（http://research.libd.org/SPEAQeasy/）。SPEAQeasy是用户友好的，降低了生物学家和临床医生对RNA-seq数据处理的计算域进入门槛，因为主要输入文件是一个包含样本名称及其相应FASTQ文件的表。其目标是为研究人员提供一个灵活的管道，无论他们的技术背景或计算环境如何，都可以立即使用。在线版本包含补充材料，可在10.1186/s12859-021-04142-3获得。
RNA sequencing (RNA-seq) is a common and widespread biological assay, and an increasing amount of data is generated with it. In practice, there are a large number of individual steps a researcher must perform before raw RNA-seq reads yield directly valuable information, such as differential gene expression data. Existing software tools are typically specialized, only performing one step–such as alignment of reads to a reference genome–of a larger workflow. The demand for a more comprehensive and reproducible workflow has led to the production of a number of publicly available RNA-seq pipelines. However, we have found that most require computational expertise to set up or share among several users, are not actively maintained, or lack features we have found to be important in our own analyses. In response to these concerns, we have developed a Scalable Pipeline for Expression Analysis and Quantification (SPEAQeasy), which is easy to install and share, and provides a bridge towards R/Bioconductor downstream analysis solutions. SPEAQeasy is portable across computational frameworks (SGE, SLURM, local, docker integration) and different configuration files are provided (http://research.libd.org/SPEAQeasy/). SPEAQeasy is user-friendly and lowers the computational-domain entry barrier for biologists and clinicians to RNA-seq data processing as the main input file is a table with sample names and their corresponding FASTQ files. The goal is to provide a flexible pipeline that is immediately usable by researchers, regardless of their technical background or computing environment. The online version contains supplementary material available at 10.1186/s12859-021-04142-3.
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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：
10.1093/bioinformatics/btu638
发表时间：
2015-01-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Anders S;Pyl PT;Huber W
通讯作者：
Huber W
影响因子：
14.9
作者：
Collado-Torres L;Nellore A;Frazee AC;Wilks C;Love MI;Langmead B;Irizarry RA;Leek JT;Jaffe AE
通讯作者：
Jaffe AE
影响因子：
14.9
作者：
Frankish A;Diekhans M;Ferreira AM;Johnson R;Jungreis I;Loveland J;Mudge JM;Sisu C;Wright J;Armstrong J;Barnes I;Berry A;Bignell A;Carbonell Sala S;Chrast J;Cunningham F;Di Domenico T;Donaldson S;Fiddes IT;García Girón C;Gonzalez JM;Grego T;Hardy M;Hourlier T;Hunt T;Izuogu OG;Lagarde J;Martin FJ;Martínez L;Mohanan S;Muir P;Navarro FCP;Parker A;Pei B;Pozo F;Ruffier M;Schmitt BM;Stapleton E;Suner MM;Sycheva I;Uszczynska-Ratajczak B;Xu J;Yates A;Zerbino D;Zhang Y;Aken B;Choudhary JS;Gerstein M;Guigó R;Hubbard TJP;Kellis M;Paten B;Reymond A;Tress ML;Flicek P
通讯作者：
Flicek P
影响因子：
16.2
作者：
Collado-Torres, Leonardo;Burke, Emily E.;Narurkar, Rujuta
通讯作者：
Narurkar, Rujuta