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REINDEER: efficient indexing of k-mer presence and abundance in sequencing datasets

View ORCID ProfileCamille Marchet, View ORCID ProfileZamin Iqbal, View ORCID ProfileDaniel Gautheret, Mikael Salson, View ORCID ProfileRayan Chikhi
doi: https://doi.org/10.1101/2020.03.29.014159
Camille Marchet
1Univ. Lille, CNRS, UMR 9189 - CRIStAL, F-59000 Lille, France
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  • ORCID record for Camille Marchet
  • For correspondence: marchetcamille@gmail.com
Zamin Iqbal
2European Bioinformatics Institute, Cambridge, UK
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Daniel Gautheret
3Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), Gif-sur-Yvette, France
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Mikael Salson
1Univ. Lille, CNRS, UMR 9189 - CRIStAL, F-59000 Lille, France
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Rayan Chikhi
4Institut Pasteur, CNRS, C3BI - USR 3756, 75015 Paris, France
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Abstract

Motivation In this work we present REINDEER, a novel computational method that performs indexing of sequences and records their abundances across a collection of datasets. To the best of our knowledge, other indexing methods have so far been unable to record abundances efficiently across large datasets.

Results We used REINDEER to index the abundances of sequences within 2,585 human RNA-seq experiments in 45 hours using only 56 GB of RAM. This makes REINDEER the first method able to record abundances at the scale of 4 billion distinct k-mers across 2,585 datasets. REINDEER also supports exact presence/absence queries of k-mers. Briefly, REINDEER constructs the compacted de Bruijn graph (DBG) of each dataset, then conceptually merges those DBGs into a single global one. Then, REINDEER constructs and indexes monotigs, which in a nutshell are groups of k-mers of similar abundances.

Availability https://github.com/kamimrcht/REINDEER

Contact camille.marchet{at}univ-lille.fr

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 16, 2020.
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REINDEER: efficient indexing of k-mer presence and abundance in sequencing datasets
Camille Marchet, Zamin Iqbal, Daniel Gautheret, Mikael Salson, Rayan Chikhi
bioRxiv 2020.03.29.014159; doi: https://doi.org/10.1101/2020.03.29.014159
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REINDEER: efficient indexing of k-mer presence and abundance in sequencing datasets
Camille Marchet, Zamin Iqbal, Daniel Gautheret, Mikael Salson, Rayan Chikhi
bioRxiv 2020.03.29.014159; doi: https://doi.org/10.1101/2020.03.29.014159

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