2013
DOI: 10.1186/gb-2013-14-8-r90
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Virmid: accurate detection of somatic mutations with sample impurity inference

Abstract: Detection of somatic variation using sequence from disease-control matched data sets is a critical first step. In many cases including cancer, however, it is hard to isolate pure disease tissue, and the impurity hinders accurate mutation analysis by disrupting overall allele frequencies. Here, we propose a new method, Virmid, that explicitly determines the level of impurity in the sample, and uses it for improved detection of somatic variation. Extensive tests on simulated and real sequencing data from breast … Show more

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Cited by 61 publications
(49 citation statements)
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“…[55][56][57][58][59] However, in vivo modeling of somatic mutations in the developing brain has been challenging given the limitations of genome-editing tools 60 and the size constraints of viral vectors. 61 In the present study, we combined in utero electroporation with the CRISPR-Cas9 system to introduce somatic genome modifications in a small fraction of neurons in the developing brain.…”
Section: Discussionmentioning
confidence: 99%
“…[55][56][57][58][59] However, in vivo modeling of somatic mutations in the developing brain has been challenging given the limitations of genome-editing tools 60 and the size constraints of viral vectors. 61 In the present study, we combined in utero electroporation with the CRISPR-Cas9 system to introduce somatic genome modifications in a small fraction of neurons in the developing brain.…”
Section: Discussionmentioning
confidence: 99%
“…The detailed sequence of primer and index are listed in Supplementary Bioinformatic analysis. We used both the Virmid (http://sourceforge.net/ projects/virmid/) and MuTect (http://www.broadinstitute.org/cancer/cga/ mutect) algorithms to jointly analyze blood-brain paired WES data sets and call any given variants that arise de novo in affected brains (not in the germline) 12,13 . Although both tools are useful for finding somatic mutations with low-allelic fraction in genetically heterogeneous samples, they are based on different probability models emerged from independent approaches.…”
Section: Mouse Care and Informationmentioning
confidence: 99%
“…To detect somatic mutations in the affected brains, we used two recently developed algorithms, Virmid (http://sourceforge.net/projects/virmid/) and MuTect (http://www. broadinstitute.org/cancer/cga/mutect), which are particularly useful Brain somatic mutations in MTOR cause focal cortical dysplasia type II leading to intractable epilepsy for detecting somatic mutations with low allelic frequencies in genetically heterogeneous tissues 12,13 .…”
mentioning
confidence: 99%
“…Prepared library was sequenced by HiSeq2000 (Illumina). Sequenced data were analyzed by Virmid to detect somatic mutations (18).…”
Section: Real-time Reverse-transcription Pcr (Rt-pcr)mentioning
confidence: 99%