RNF: a general framework to evaluate NGS read mappers

Abstract : Motivation: Read simulators combined with alignment evaluation tools provide the most straightforward way to evaluate and compare mappers. Simulation of reads is accompanied by information about their positions in the source genome. This information is then used to evaluate alignments produced by the mapper. Finally, reports containing statistics of successful read alignments are created. In default of standards for encoding read origins, every evaluation tool has to be made explicitly compatible with the simulator used to generate reads. Results: To solve this obstacle, we have created a generic format Read Naming Format (RNF) for assigning read names with encoded information about original positions. Futhermore, we have developed an associated software package RNFTools containing two principal components. MISHMASH applies one of popular read simulating tools (among DWGSIM, ART, MASON, CURESIM, etc.) and transforms the generated reads into RNF format. LAVENDER evaluates then a given read mapper using simulated reads in RNF format. A special attention is payed to mapping qualities that serve for parametrization of ROC curves, and to evaluation of the effect of read sample contamination. Availability and implementation: RNFTools: http://karel-brinda.github.io/rnftools Spec. of RNF: http://karel-brinda.github.io/rnf-spec Contact: karel.brinda@univ-mlv.fr
Type de document :
Article dans une revue
Bioinformatics, Oxford University Press (OUP), 2016, 32 (1), pp.136-139. 〈10.1093/bioinformatics/btv524〉
Liste complète des métadonnées

Littérature citée [14 références]  Voir  Masquer  Télécharger

Contributeur : Karel Břinda <>
Soumis le : lundi 4 avril 2016 - 16:36:46
Dernière modification le : samedi 17 février 2018 - 17:46:02
Document(s) archivé(s) le : mardi 5 juillet 2016 - 15:42:25


Fichiers produits par l'(les) auteur(s)



Karel Břinda, Valentina Boeva, Gregory Kucherov. RNF: a general framework to evaluate NGS read mappers. Bioinformatics, Oxford University Press (OUP), 2016, 32 (1), pp.136-139. 〈10.1093/bioinformatics/btv524〉. 〈hal-01220199v2〉



Consultations de la notice


Téléchargements de fichiers