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Related Experiment Video

Updated: Nov 1, 2025

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level
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lra: A long read aligner for sequences and contigs.

Jingwen Ren1, Mark J P Chaisson1

  • 1Department of Quantitative and Computational Biology (QCB), University of Southern California, Los Angeles, California, the United States of America.

Plos Computational Biology
|June 21, 2021
PubMed
Summary

Detecting genetic variation with long sequencing reads is challenging. A new method, lra, uses sparse dynamic programming with a concave gap penalty to improve structural variant discovery from PacBio and Oxford Nanopore (ONT) data.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Aligning single-molecule sequencing (SMS) reads for variation detection is computationally intensive.
  • Standard sparse dynamic programming (SDP) uses linear gap penalties, which do not accurately model biological variation.

Purpose of the Study:

  • To develop and evaluate a novel alignment method, lra, that utilizes SDP with a concave-cost gap penalty for improved structural variant (SV) discovery.

Main Methods:

  • Implemented lra using SDP with a concave-cost gap penalty.
  • Applied lra to align long-read sequences from PacBio and Oxford Nanopore (ONT) instruments.
  • Assessed lra's performance in detecting structural variants (SVs) and calling variation from de novo assembly contigs.

Main Results:

  • lra enhances sensitivity and specificity for SV discovery, especially for variants >1kb and from ONT reads.
  • Runtime of lra is comparable to existing methods (1.05-3.76×).
  • lra achieved a 3.2% increase in Truvari F1 score for variation calling from assembly contigs compared to minimap2+htsbox.

Conclusions:

  • lra provides a more accurate and sensitive approach for structural variant detection using long-read sequencing data.
  • The method demonstrates improved performance for challenging datasets, including Oxford Nanopore reads and de novo assemblies.
  • lra is a valuable tool for genomic variation analysis, available via bioconda and GitHub.