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elPrep 4: A multithreaded framework for sequence analysis.

Charlotte Herzeel1, Pascal Costanza1, Dries Decap1,2

  • 1ExaScience Life Lab, IMEC, Leuven, Belgium.

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|February 14, 2019
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Summary
This summary is machine-generated.

elPrep 4, a new Go implementation, processes sequence alignment map files for variant calling. It significantly speeds up GATK Best Practices preparation steps, offering faster runtimes and reduced resource use.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Sequence alignment map (SAM) files are crucial for genomic data analysis.
  • Existing tools for SAM file processing can be resource-intensive and slow.
  • The Genome Analysis Toolkit (GATK) Best Practices pipelines require extensive data preparation.

Purpose of the Study:

  • To develop a faster and more efficient framework for processing SAM files.
  • To implement all GATK Best Practices preparation steps in a new tool.
  • To improve runtime and resource utilization for variant calling pipelines.

Main Methods:

  • Reimplementation of the elPrep framework from scratch in the Go programming language (elPrep 4).
  • Incorporation of new and improved functionalities for sorting, duplicate marking, base quality score recalibration, and file parsing.
  • Redesign of underlying algorithms to leverage parallel execution for enhanced performance.

Main Results:

  • elPrep 4 successfully processes all GATK Best Practices preparation steps.
  • Performance benchmarks show elPrep 4 is up to 13x faster for Whole Exome Sequencing (WES) and 7.4x faster for Whole Genome Sequencing (WGS) data compared to GATK 4.
  • elPrep 4 utilizes fewer computational resources than existing tools.

Conclusions:

  • elPrep 4 offers a significant improvement in speed and efficiency for genomic data preparation.
  • The tool faithfully reproduces GATK 4 outcomes while providing substantial performance gains.
  • elPrep 4 is a valuable tool for accelerating variant calling workflows in genomics research.