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# Mapping-friendly Sequence Reductions to process compressed genomic data

Roland Faure, Baptiste Hilaire, Dominique Lavenier

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## To cite this version:

Roland Faure, Baptiste Hilaire, Dominique Lavenier. Mapping-friendly Sequence Reductions to process compressed genomic data. SeqBIM 2023, Nov 2023, Lille, France. pp.1-1. hal-04272505

HAL Id: hal-04272505

https://hal.science/hal-04272505v1

Submitted on 6 Nov 2023

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Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
Abstract

Mapping-friendly Sequence Reductions
to process compressed genomic data

Roland Faure<fnref n="1" />,<fnref n="2" />*, Baptiste Hilaire<fnref n="1" />, Dominique Lavenier<fnref n="1" />

Abstract

Efficiently managing vast DNA datasets necessitates the development of highly
effective sequence compression techniques to reduce storage and computational
requirements. We propose here to explore the potential of a lossy compression technique,
Mapping-friendly Sequence Reductions (MSRs).

MSRs were introduced in [1] as a generalization of homopolymer compression to
improve the accuracy of alignment tools. Essentially, MSRs deterministically transform
sequences into shorter counterparts, in such a way that if an original query and a target
sequence align, their reduced forms will align as well. While homopolymer compression is
one example of an MSR, numerous others exist, potentially offering substantial sequence
length reduction—such as retaining only bases between 'A' and 'T' (on average, 1 base out
of 16): AACAGTGACACTAAACT → GCC. These rapid computations yield lossy
representations of the originals. Notably, the reduced sequences can be stored, aligned,
assembled, and indexed much like regular sequences.

MSRs could be used to improve the efficiency of taxonomic classification tools, by
indexing and querying reduced sequences. Our experimentation with a toy example, a
mixture of 10 *E. coli* strains, demonstrates that this approach can yield greater precision
than indexing and querying a reduced portion of k-mers (typically minimizers).
Specifically, using the reduction described above, 76% of reduced 31-mers were unique,
whereas only 47% of not-reduced 31-mers were.

In our presentation, we will also explore other tasks that could benefit from sequence
reduction, such as mapping, genome assembly, and structural variant detection.

References

<footnote n="1">¹Univ. Rennes, Inria RBA, CNRS UMR 6074, Rennes, France</footnote>

<footnote n="2">²Evolution Biologique et Ecologie, Université libre de Bruxelles (ULB), Brussels, Belgium</footnote>

<footnote>*Corresponding author: roland.faure@irisa.fr</footnote>

<footnote>[1] Blassel L, Medvedev P, Chikhi R. Mapping-friendly sequence reductions: Going beyond homopolymer compression. iScience. 2022 Oct 13;25(11):105305.</footnote>