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SAMSA2:一个独立的宏转录组分析管道。

SAMSA2: a standalone metatranscriptome analysis pipeline.

机构信息

Genome Center, University of California, Davis, California, USA.

Department of Food Science and Technology, University of California, Davis, California, USA.

出版信息

BMC Bioinformatics. 2018 May 21;19(1):175. doi: 10.1186/s12859-018-2189-z.

Abstract

BACKGROUND

Complex microbial communities are an area of growing interest in biology. Metatranscriptomics allows researchers to quantify microbial gene expression in an environmental sample via high-throughput sequencing. Metatranscriptomic experiments are computationally intensive because the experiments generate a large volume of sequence data and each sequence must be compared with reference sequences from thousands of organisms.

RESULTS

SAMSA2 is an upgrade to the original Simple Annotation of Metatranscriptomes by Sequence Analysis (SAMSA) pipeline that has been redesigned for standalone use on a supercomputing cluster. SAMSA2 is faster due to the use of the DIAMOND aligner, and more flexible and reproducible because it uses local databases. SAMSA2 is available with detailed documentation, and example input and output files along with examples of master scripts for full pipeline execution.

CONCLUSIONS

SAMSA2 is a rapid and efficient metatranscriptome pipeline for analyzing large RNA-seq datasets in a supercomputing cluster environment. SAMSA2 provides simplified output that can be examined directly or used for further analyses, and its reference databases may be upgraded, altered or customized to fit the needs of any experiment.

摘要

背景

复杂的微生物群落是生物学中一个日益增长的研究领域。宏转录组学允许研究人员通过高通量测序来定量环境样本中的微生物基因表达。宏转录组学实验计算量很大,因为实验会产生大量的序列数据,并且每个序列都必须与来自数千种生物体的参考序列进行比较。

结果

SAMSA2 是对原始 Simple Annotation of Metatranscriptomes by Sequence Analysis(SAMSA)管道的升级,该管道经过重新设计,可以在超级计算集群上独立使用。由于使用了 DIAMOND 比对器,SAMSA2 更快,并且由于使用了本地数据库,因此更灵活、更具可重复性。SAMSA2 提供了详细的文档,以及示例输入和输出文件,以及完整管道执行的主脚本示例。

结论

SAMSA2 是一个快速高效的宏转录组学管道,可在超级计算集群环境中分析大型 RNA-seq 数据集。SAMSA2 提供了简化的输出,可以直接检查或用于进一步分析,并且其参考数据库可以升级、更改或定制,以满足任何实验的需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9d6/5963165/43af684ab19b/12859_2018_2189_Fig1_HTML.jpg

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