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BigSeqKit: a parallel Big Data toolkit to process FASTA and FASTQ files at scale.

César Piñeiro1, Juan C Pichel1

  • 1CiTIUS, Universidade de Santiago de Compostela, Santiago de Compostela 15782, Spain.

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|July 31, 2023
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Summary

BigSeqKit accelerates the processing of large sequencing data (FASTA/FASTQ files) by leveraging high-performance computing. This toolkit offers significant speedups compared to existing methods for bioinformatics analysis.

Keywords:
Big DataFASTA/FASTQ filesParallelismPerformance

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput sequencing generates massive datasets, typically in FASTA/FASTQ formats.
  • Existing tools struggle with efficient processing of very large sequencing files due to sequential processing limitations.
  • Current parallelization in tools like seqkit is limited to a few threads on a single node.

Purpose of the Study:

  • To develop a highly efficient toolkit for manipulating large FASTA/FASTQ files.
  • To overcome the scalability limitations of existing sequence data processing tools.
  • To enable faster transformation of sequence data into biological insights.

Main Methods:

  • Utilized a high-performance computing-Big Data framework.
  • Parallelized and optimized commands from the seqkit tool.
  • Developed BigSeqKit as a user-friendly toolkit and bioinformatics library.

Main Results:

  • BigSeqKit demonstrates substantial speed improvements, often tens to hundreds of times faster than state-of-the-art tools.
  • The toolkit is designed for efficient parallel processing of terabyte-scale sequencing files.
  • BigSeqKit is easy to install and use on various hardware platforms.

Conclusions:

  • BigSeqKit is a comprehensive and ultra-fast toolkit for large-scale FASTA/FASTQ file manipulation.
  • It significantly enhances the efficiency of processing massive sequencing data.
  • The toolkit is publicly available for use in bioinformatics research.