Mobster: accurate detection of mobile element insertions in next generation sequencing data

Djie T.jwan Thung, Joep de Ligt, Lisenka E.M. Vissers, Marloes Steehouwer, Mark Kroon, Petra de Vries, Eline P. Slagboom, Kai Ye, Joris A. Veltman, Jayne Y. Hehir-Kwa

Onderzoeksoutput: Bijdrage aan tijdschriftArtikelpeer review

72 Citaten (Scopus)

Samenvatting

Mobile elements are major drivers in changing genomic architecture and can cause disease. The detection of mobile elements is hindered due to the low mappability of their highly repetitive sequences. We have developed an algorithm, called Mobster, to detect non-reference mobile element insertions in next generation sequencing data from both whole genome and whole exome studies. Mobster uses discordant read pairs and clipped reads in combination with consensus sequences of known active mobile elements. Mobster has a low false discovery rateand high recall rate for both L1 and Alu elements. Mobster is available at http://sourceforge.net/projects/mobster.

Originele taal-2Engels
Artikelnummer488
Pagina's (van-tot)488
Aantal pagina's1
TijdschriftGenome Biology
Volume15
Nummer van het tijdschrift10
DOI's
StatusGepubliceerd - 2014
Extern gepubliceerdJa

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