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SOAPnuke: a MapReduce acceleration-supported software for integrated quality control and preprocessing of

Yuxin Chen1, Yongsheng Chen2, Chunmei Shi3,4,5

  • 1BGI-Shenzhen, Shenzhen 518083.

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|December 9, 2017
PubMed
Summary

SOAPnuke offers comprehensive quality control (QC) and preprocessing for sequencing data analysis. This tool integrates multiple functions into a single executable and utilizes a MapReduce framework for highly scalable acceleration, improving analysis speed.

Keywords:
MapReducehigh-throughput sequencingpreprocessingquality control

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Quality control (QC) and preprocessing are critical for accurate sequencing data analysis.
  • Existing tools lack integrated comprehensive functions, robust architectures, and scalable acceleration.

Purpose of the Study:

  • Introduce SOAPnuke, a novel tool for integrated sequencing data QC and preprocessing.
  • Address limitations of current tools by providing a unified, scalable solution.

Main Methods:

  • SOAPnuke features a "QC-Preprocess-QC" workflow with four specialized modules for different sequencing data types (genomic, small RNA, DGE, metagenomic).
  • Implemented a MapReduce acceleration framework for distributed processing across compute clusters.
  • Conducted benchmarking using a NA12878 dataset against other preprocessing tools.

Main Results:

  • SOAPnuke centralizes processing, eliminating file reformatting between steps.
  • Standalone SOAPnuke balances resource usage and performance.
  • MapReduce-accelerated SOAPnuke achieved approximately 5.7 times the speed of other tools on a 16-node cluster.

Conclusions:

  • SOAPnuke provides an efficient, scalable, and integrated solution for sequencing data QC and preprocessing.
  • The MapReduce framework significantly enhances processing speed for large datasets.
  • SOAPnuke is a valuable tool for genomic, small RNA, DGE, and metagenomic data analysis.