Indexing labeled sequences

Tatiana Rocher; Mathieu Giraud; Mikaël Salson

doi:10.7717/peerj-cs.148

Indexing labeled sequences

PeerJ Comput Sci. 2018 Mar 26:4:e148. doi: 10.7717/peerj-cs.148. eCollection 2018.

Authors

Tatiana Rocher¹, Mathieu Giraud¹, Mikaël Salson¹

Affiliation

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

Abstract

Background: Labels are a way to add some information on a text, such as functional annotations such as genes on a DNA sequences. V(D)J recombinations are DNA recombinations involving two or three short genes in lymphocytes. Sequencing this short region (500 bp or less) produces labeled sequences and brings insight in the lymphocyte repertoire for onco-hematology or immunology studies.

Methods: We present two indexes for a text with non-overlapping labels. They store the text in a Burrows-Wheeler transform (BWT) and a compressed label sequence in a Wavelet Tree. The label sequence is taken in the order of the text (TL-index) or in the order of the BWT (TL_BW-index). Both indexes need a space related to the entropy of the labeled text.

Results: These indexes allow efficient text-label queries to count and find labeled patterns. The TL_BW-index has an overhead on simple label queries but is very efficient on combined pattern-label queries. We implemented the indexes in C++ and compared them against a baseline solution on pseudo-random as well as on V(D)J labeled texts.

Discussion: New indexes such as the ones we proposed improve the way we index and query labeled texts as, for instance, lymphocyte repertoire for hematological and immunological studies.

Keywords: Burrows–Wheeler transform; Data structures; Text indexing; V(D)J recombination; Wavelet Tree.

Grants and funding

This work was supported by Université de Lille, SIRIC ONCOLille, and Région Hauts-de-France. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.