Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1089/cmb.2018.0007
Titel (primär) ShRangeSim: Simulation of single nucleotide polymorphism clusters in next-generation sequencing data
Autor Boenn, M.
Quelle Journal of Computational Biology
Erscheinungsjahr 2018
Department BOOEK; iDiv
Band/Volume 25
Heft 6
Seite von 613
Seite bis 622
Sprache englisch
Keywords next-generation sequencing; overdispersion; simulation; SNP cluster
Abstract

Genomic variations are in the focus of research to uncover mechanisms of host–pathogen interactions and diseases such as cancer. Nowadays, next-generation sequencing (NGS) data are analyzed through dedicated pipelines to detect them. Surrogate NGS data in conjunction with genomic variations help to evaluate pipelines and validate their outcomes, fostering selection of proper tools for a given scientific question. I describe how existing approaches for simulating NGS data in conjunction with genomic variations fail to model local enrichments of single nucleotide polymorphisms (SNPs), so called SNP clusters. Two distributions for count data are applied to publicly available collections of genomic variations. The results suggest modeling of SNP cluster sizes by overdispersion-aware distributions.

dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=20247
Boenn, M. (2018):
ShRangeSim: Simulation of single nucleotide polymorphism clusters in next-generation sequencing data
J. Comput. Biol. 25 (6), 613 - 622 10.1089/cmb.2018.0007