Sequencing technologies and tools for short tandem repeat variation detection

Minh Duc Cao, Sureshkumar Balasubramanian, Mikael Boden

Research output: Contribution to journalArticleResearchpeer-review

11 Citations (Scopus)

Abstract

Short tandemrepeats are highly polymorphic and associated with a wide range of phenotypic variation, some of which cause neurodegenerative disease in humans. With advances in high-throughput sequencing technologies, there are novel opportunities to study genetic variation. While available sequencing technologies and bioinformatics tools provide options for mining high-throughput sequencing data, their suitability for analysis of repeat variation is an open question, with tools for quantifying variability in repetitive sequence still in their infancy. We present here a comprehensive survey and empirical evaluation of current sequencing technologies and bioinformatics tools in all stages of an analysis pipeline. While there is not one optimal pipeline to suit all circumstances, we find that the choice of alignment and repeat genotyping tools greatly impacts the accuracy and efficiency by which short tandem repeat variation can be detected. We further note that to detect variation relevant to many repeat diseases, it is essential to choose technologies that offer either long read-lengths or paired-end sequencing, coupled with specific genotyping tools.
Original languageEnglish
Pages (from-to)193 - 204
Number of pages12
JournalBriefings in Bioinformatics
Volume16
Issue number2
DOIs
Publication statusPublished - 2015

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