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MMR: a tool for read multi-mapper resolution.

André Kahles1, Jonas Behr1, Gunnar Rätsch1

  • 1Memorial Sloan Kettering Cancer Center, Computational Biology Center, 1275 York Avenue, New York, NY 10065, USA.

Bioinformatics (Oxford, England)
|November 1, 2015
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Summary
This summary is machine-generated.

The multi-mapper resolution (MMR) tool resolves ambiguous read mappings in high-throughput sequencing data. This improves downstream analysis accuracy and efficiency, reducing file sizes and processing times.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput sequencing data analysis relies on accurate genome mapping.
  • Ambiguous read mappings (ties) present a significant challenge in alignment and downstream analyses.
  • Existing methods struggle to optimally resolve equally mapping locations.

Purpose of the Study:

  • To introduce the multi-mapper resolution (MMR) tool for resolving ambiguous read mappings.
  • To improve the accuracy and efficiency of genomic and transcriptomic data analysis pipelines.
  • To provide a computationally efficient post-processing step for alignment files.

Main Methods:

  • The MMR tool infers optimal mapping locations using coverage density from other mapped reads.
  • It functions as a post-processing step for existing alignment files in BAM format.
  • The algorithm exhibits linear complexity with respect to the number of alignments.

Main Results:

  • MMR filtering significantly enhances downstream analysis performance, including transcript quantitation and differential testing.
  • Transcript quantitation accuracy (Spearman correlation) improved by 15% for 51-base pair reads.
  • Alignment file sizes were reduced by over 50%, leading to decreased quantification tool running times.

Conclusions:

  • MMR effectively resolves multi-mapping challenges in high-throughput sequencing data.
  • The tool offers substantial improvements in accuracy and computational efficiency for genomic analyses.
  • MMR is an easily applicable, open-source solution for enhancing existing analysis workflows.