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Lacking alignments? The next-generation sequencing mapper segemehl revisited.

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  • 1Transcriptome Bioinformatics Junior Research Group, LIFE-Leipzig Research Center for Civilization Diseases, Interdisciplinary Center for Bioinformatics, Bioinformatics Group, Department of Computer Science, University Leipzig, RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany, Santa Fe Institute, Santa Fe, New Mexico, USA, Department of Theoretical Chemistry, University of Vienna, Austria, Max-Planck-Institute for Mathematics in Sciences, Leipzig, Germany and Center for non-coding RNA in Technology and Health, University of Copenhagen, DenmarkTranscriptome Bioinformatics Junior Research Group, LIFE-Leipzig Research Center for Civilization Diseases, Interdisciplinary Center for Bioinformatics, Bioinformatics Group, Department of Computer Science, University Leipzig, RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany, Santa Fe Institute, Santa Fe, New Mexico, USA, Department of Theoretical Chemistry, University of Vienna, Austria, Max-Planck-Institute for Mathematics in Sciences, Leipzig, Germany and Center for non-coding RNA in Technology and Health, University of Copenhagen, Denmark.

Bioinformatics (Oxford, England)
|March 15, 2014
PubMed
Summary

We benchmarked segemehl, a read aligner, against other tools. We also introduced lack, a new tool to rescue unmapped RNA-seq reads, improving bioinformatics analysis for genomic and transcriptomic investigations.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Next-generation sequencing (NGS) is pivotal in molecular biology.
  • NGS enables investigation of genomic, transcriptomic, and epigenomic features.
  • Read mapping to reference genomes is a critical initial bioinformatics step for NGS data.

Purpose of the Study:

  • To benchmark the performance of the segemehl read aligner.
  • To introduce and evaluate the lack tool for rescuing unmapped RNA-seq reads.
  • To provide improved bioinformatics tools for NGS data analysis.

Main Methods:

  • Comparative benchmarking of the segemehl read aligner against state-of-the-art methods.
  • Development and integration of the lack tool with segemehl and other split-read aligners.
  • Evaluation of read mapping and rescue capabilities.

Main Results:

  • Segemehl demonstrated competitive performance in read alignment benchmarks.
  • The lack tool effectively rescues unmapped RNA-seq reads.
  • lack enhances the utility of segemehl and other aligners for transcriptomic analysis.

Conclusions:

  • Segemehl is a robust tool for read alignment in NGS workflows.
  • The addition of lack significantly improves the analysis of RNA-sequencing data by rescuing unmapped reads.
  • These tools offer valuable advancements for genomic and transcriptomic research.