MersV1, Main, Exploration, bibRecord, 000D39

Improving the performance of minimizers and winnowing schemes

Identifieur interne : 000D39 ( Main/Exploration ); précédent : 000D38; suivant : 000D40

Improving the performance of minimizers and winnowing schemes

Auteurs : Guillaume Marçais [États-Unis] ; David Pellow [Israël] ; Daniel Bork [États-Unis] ; Yaron Orenstein [États-Unis] ; Ron Shamir [Israël] ; Carl Kingsford [États-Unis]

Source :

Bioinformatics [ 1367-4803 ] ; 2017.

RBID : PMC:5870760

Descripteurs français

KwdFr :
- Algorithmes, Analyse de séquence d'ADN (), Génome humain, Génomique (), Humains, Logiciel.
MESH :
- Algorithmes, Analyse de séquence d'ADN, Génome humain, Génomique, Humains, Logiciel.

English descriptors

KwdEn :
- Algorithms, Genome, Human, Genomics (methods), Humans, Sequence Analysis, DNA (methods), Software.
MESH :
- methods : Genomics, Sequence Analysis, DNA.
- Algorithms, Genome, Human, Humans, Software.

Abstract

AbstractMotivation

The minimizers scheme is a method for selecting k-mers from sequences. It is used in many bioinformatics software tools to bin comparable sequences or to sample a sequence in a deterministic fashion at approximately regular intervals, in order to reduce memory consumption and processing time. Although very useful, the minimizers selection procedure has undesirable behaviors (e.g. too many k-mers are selected when processing certain sequences). Some of these problems were already known to the authors of the minimizers technique, and the natural lexicographic ordering of k-mers used by minimizers was recognized as their origin. Many software tools using minimizers employ ad hoc variations of the lexicographic order to alleviate those issues.

Results

We provide an in-depth analysis of the effect of k-mer ordering on the performance of the minimizers technique. By using small universal hitting sets (a recently defined concept), we show how to significantly improve the performance of minimizers and avoid some of its worse behaviors. Based on these results, we encourage bioinformatics software developers to use an ordering based on a universal hitting set or, if not possible, a randomized ordering, rather than the lexicographic order. This analysis also settles negatively a conjecture (by Schleimer et al.) on the expected density of minimizers in a random sequence.

Availability and Implementation

The software used for this analysis is available on GitHub: https://github.com/gmarcais/minimizers.git.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870760

DOI: 10.1093/bioinformatics/btx235
PubMed: 28881970
PubMed Central: 5870760

Affiliations:

Le document en format XML

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<p>The minimizers scheme is a method for selecting <italic>k</italic>
-mers from sequences. It is used in many bioinformatics software tools to bin comparable sequences or to sample a sequence in a deterministic fashion at approximately regular intervals, in order to reduce memory consumption and processing time. Although very useful, the minimizers selection procedure has undesirable behaviors (e.g. too many <italic>k</italic>
-mers are selected when processing certain sequences). Some of these problems were already known to the authors of the minimizers technique, and the natural lexicographic ordering of <italic>k</italic>
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<p>We provide an in-depth analysis of the effect of <italic>k</italic>
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Serveur d'exploration MERS

Improving the performance of minimizers and winnowing schemes

Improving the performance of minimizers and winnowing schemes

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

Pour générer des pages wiki

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