GIST Scholar
College of Artificial Intelligence
Department of Electrical Engineering and Computer Science
1. Journal Articles
Virmid: accurate detection of somatic mutations with sample impurity inference
- Type
- Article
- Citation
- GENOME BIOLOGY, v.14, no.8
- Issued Date
- 2013-12
- 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 cancer and hemimegalencephaly demonstrate the power of our model. A software implementation of our method is available at http://sourceforge.net/projects/virmid/.
- Publisher
- BioMed Central
- ISSN
- 1474-7596
- Appears in Collections:
- Department of Electrical Engineering and Computer Science > 1. Journal Articles
- Files in This Item:
-
-
There are no files associated with this item.
-
Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.