Back to sequences: Find the origin of k-mers

A vast majority of bioinformatics tools dedicated to the treatment of raw sequencing data heavily use the concept of -mers, which are words of length .This enables us to reduce the redundancy of data (and thus the memory pressure), to discard sequencing errors, and to dispose of objects of fixed size that can be easily manipulated and compared to each other.A drawback is that the link between each -mer and the original set of sequences to which it belongs is lost.Given the volume of data considered in this context, recovering this association is costly.In this work, we present "back_to_sequences", a simple tool designed to index a set of -mers of interest and to stream a set of sequences, extracting those containing at least one of the indexed -mer.In addition, the occurrence positions of -mers in the sequences can be provided.Our results show that back_to_sequences streams 200 short reads per millisecond, allowing to search -mers in hundreds of millions of reads in a matter of a few minutes.

Authors

Institutions

Publication Details

Journal
The Journal of Open Source Software
Published
2024-09-23
DOI
https://doi.org/10.21105/joss.07066
Citations
4
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.94

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Back to sequences: Find the origin of k-mers

Pierre Peterlongo, Francesco Andreace, Pierre Marijon, Anthony Baire
4 citations
The Journal of Open Source Software
Genomics and Phylogenetic Studies
0.94
article

Back to sequences: Find the origin of k-mers

Pierre Peterlongo, Francesco Andreace, Pierre Marijon, Anthony Baire
article en
4 citations

Abstract

A vast majority of bioinformatics tools dedicated to the treatment of raw sequencing data heavily use the concept of -mers, which are words of length .This enables us to reduce the redundancy of data (and thus the memory pressure), to discard sequencing errors, and to dispose of objects of fixed size that can be easily manipulated and compared to each other.A drawback is that the link between each -mer and the original set of sequences to which it belongs is lost.Given the volume of data considered in this context, recovering this association is costly.In this work, we present "back_to_sequences", a simple tool designed to index a set of -mers of interest and to stream a set of sequences, extracting those containing at least one of the indexed -mer.In addition, the occurrence positions of -mers in the sequences can be provided.Our results show that back_to_sequences streams 200 short reads per millisecond, allowing to search -mers in hundreds of millions of reads in a matter of a few minutes.

The Journal of Open Source SoftwareVol. 9(101)
Institut de Recherche en Informatique et Systèmes Aléatoires (FR), Biologie Computationnelle, Quantitative et Synthétique (FR)
Agence Nationale de la Recherche
Openalex Percentile: Top 25%
Genomics and Phylogenetic Studies
0.94
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.