Biospark: scalable analysis of large numerical datasets from biological simulations and experiments using Hadoop and Spark.

ABSTRACT: Data-parallel programming techniques can dramatically decrease the time needed to analyze large datasets. While these methods have provided significant improvements for sequencing-based analyses, other areas of biological informatics have not yet adopted them. Here, we introduce Biospark, a new framework for performing data-parallel analysis on large numerical datasets. Biospark builds upon the open source Hadoop and Spark projects, bringing domain-specific features for biology.

Availability and implementation

Source code is licensed under the Apache 2.0 open source license and is available at the project website: https://www.assembla.com/spaces/roberts-lab-public/wiki/Biospark CONTACT: [e-mail] information: Supplementary data are available at Bioinformatics onl

SUBMITTER: Klein M 

PROVIDER: S-EPMC6276899 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature