SeqPig: simple and scalable scripting for large sequencing data sets in Hadoop

被引:58
作者
Schumacher, Andre [1 ,2 ]
Pireddu, Luca [3 ]
Niemenmaa, Matti [1 ]
Kallio, Aleksi
Korpelainen, Eija
Zanetti, Gianluigi [3 ]
Heljanko, Keijo [1 ]
机构
[1] Aalto Univ, Sch Sci, Espoo, Finland
[2] Int Comp Sci Inst, Berkeley, CA 94704 USA
[3] CRS4 Ctr Adv Studies Res & Dev, Sardinia, Italy
基金
芬兰科学院;
关键词
D O I
10.1093/bioinformatics/btt601
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Hadoop MapReduce-based approaches have become increasingly popular due to their scalability in processing large sequencing datasets. However, as these methods typically require in-depth expertise in Hadoop and Java, they are still out of reach of many bioinformaticians. To solve this problem, we have created SeqPig, a library and a collection of tools to manipulate, analyze and query sequencing datasets in a scalable and simple manner. SeqPigscripts use the Hadoop-based distributed scripting engine Apache Pig, which automatically parallelizes and distributes data processing tasks. We demonstrate SeqPig's scalability over many computing nodes and illustrate its use with example scripts.
引用
收藏
页码:119 / 120
页数:2
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