popSTR: population-scale detection of STR variants

Snædís Kristmundsdóttir, Brynja D. Sigurpálsdóttir, Birte Kehr, Bjarni V. Halldórsson

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Motivation: Microsatellites, also known as short tandem repeats (STRs), are tracts of repetitive DNA sequences containing motifs ranging from two to six bases. Microsatellites are one of the most abundant type of variation in the human genome, after single nucleotide polymorphisms (SNPs) and Indels. Microsatellite analysis has a wide range of applications, including medical genetics, forensics and construction of genetic genealogy. However, microsatellite variations are rarely considered in whole-genome sequencing studies, in large due to a lack of tools capable of analyzing them.

Results: Here we present a microsatellite genotyper, optimized for Illumina WGS data, which is both faster and more accurate than other methods previously presented. There are two main ingredients to our improvements. First we reduce the amount of sequencing data necessary for creating microsatellite profiles by using previously aligned sequencing data. Second, we use population information to train microsatellite and individual specific error profiles. By comparing our genotyping results to genotypes generated by capillary electrophoresis we show that our error rates are 50% lower than those of lobSTR, another program specifically developed to determine microsatellite genotypes.

Availability and Implementation: Source code is available on Github: https://github.com/DecodeGenetics/popSTR.

Contact: [email protected] or [email protected].

Original languageEnglish
Pages (from-to)4041-4048
Number of pages8
JournalBioinformatics (Oxford, England)
Volume33
Issue number24
DOIs
Publication statusPublished - 15 Dec 2017

Bibliographical note

Publisher Copyright:
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: [email protected]

Fingerprint

Dive into the research topics of 'popSTR: population-scale detection of STR variants'. Together they form a unique fingerprint.

Cite this