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Indexing labeled sequences.

Tatiana Rocher1, Mathieu Giraud1, Mikaël Salson1

  • 1Université de Lille, CNRS, Centrale Lille, Inria, UMR 9189 CRIStAL, Lille, France.

Peerj. Computer Science
|April 5, 2021
PubMed
Summary
This summary is machine-generated.

New indexes efficiently query labeled DNA sequences, aiding immunology and onco-hematology studies of lymphocyte repertoires. These methods improve data analysis for V(D)J recombination research.

Keywords:
Burrows–Wheeler transformData structuresText indexingV(D)J recombinationWavelet Tree

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Labels provide functional annotations for biological sequences like DNA.
  • V(D)J recombination in lymphocytes involves short gene segments, crucial for immune system studies.
  • Sequencing these regions yields labeled sequences, offering insights into lymphocyte repertoires for immunology and onco-hematology.

Purpose of the Study:

  • To introduce novel indexing methods for texts with non-overlapping labels.
  • To enhance the efficiency of querying labeled sequences, particularly in biological contexts.
  • To provide tools for analyzing lymphocyte repertoire data from V(D)J recombination studies.

Main Methods:

  • Developed two indexes: TL-index and TLBW-index, utilizing Burrows-Wheeler Transform (BWT) and Wavelet Trees.
  • Indexes store text and compressed label sequences, with space complexity related to labeled text entropy.
  • Implemented indexes in C++ for performance evaluation.

Main Results:

  • Indexes enable efficient counting and locating of labeled patterns within texts.
  • TLBW-index excels in combined pattern-label queries, despite a slight overhead for simple label queries.
  • Performance was validated against a baseline on both synthetic and V(D)J recombination datasets.

Conclusions:

  • The proposed indexes significantly improve the indexing and querying of labeled texts.
  • These advancements are particularly beneficial for analyzing lymphocyte repertoires in hematological and immunological research.
  • The methods offer a more efficient approach to handling complex biological sequence data.