Archive

  • Visit JGI.DOE.GOV
News & Publications
Home › Publications › SpaRC: scalable sequence clustering using Apache Spark

SpaRC: scalable sequence clustering using Apache Spark

Published in:

Bioinformatics 35(5) , 760-768 (Mar 1 2019)

Author(s):

Shi, L., Meng, X., Tseng, E., Mascagni, M., Wang, Z.

DOI:

10.1093/bioinformatics/bty733

Abstract:

MOTIVATION: Whole genome shotgun based next-generation transcriptomics and metagenomics studies often generate 100-1000 GB sequence data derived from tens of thousands of different genes or microbial species. Assembly of these data sets requires tradeoffs between scalability and accuracy. Current assembly methods optimized for scalability often sacrifice accuracy and vice versa. An ideal solution would both scale and produce optimal accuracy for individual genes or genomes. RESULTS: Here we describe an Apache Spark-based scalable sequence clustering application, SparkReadClust (SpaRC), that partitions reads based on their molecule of origin to enable downstream assembly optimization. SpaRC produces high clustering performance on transcriptomes and metagenomes from both short and long read sequencing technologies. It achieves near-linear scalability with input data size and number of compute nodes. SpaRC can run on both cloud computing and HPC environments without modification while delivering similar performance. Our results demonstrate that SpaRC provides a scalable solution for clustering billions of reads from next-generation sequencing experiments, and Apache Spark represents a cost-effective solution with rapid development/deployment cycles for similar large-scale sequence data analysis problems. AVAILABILITY AND IMPLEMENTATION: https://bitbucket.org/berkeleylab/jgi-sparc.

View Publication

Share this:

  • Click to share on Facebook (Opens in new window)
  • Click to share on LinkedIn (Opens in new window)
  • Click to share on Pinterest (Opens in new window)
  • Click to share on Twitter (Opens in new window)
  • Click to print (Opens in new window)
  • JGI.DOE.GOV
  • Disclaimer
  • Accessibility / Section 508
Lawrence Berkeley National Lab Biosciences Area
A project of the US Department of Energy, Office of Science

JGI is a DOE Office of Science User Facility managed by Lawrence Berkeley National Laboratory

© 1997-2025 The Regents of the University of California