DeNovoGear：从头缺失和点突变发现及相位分析。
DeNovoGear: de novo indel and point mutation discovery and phasing.
机构信息
1] Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA. [2].
出版信息
Nat Methods. 2013 Oct;10(10):985-7. doi: 10.1038/nmeth.2611. Epub 2013 Aug 25.
Abstract
We present DeNovoGear software for analyzing de novo mutations from familial and somatic tissue sequencing data. DeNovoGear uses likelihood-based error modeling to reduce the false positive rate of mutation discovery in exome analysis and fragment information to identify the parental origin of germ-line mutations. We used DeNovoGear on human whole-genome sequencing data to produce a set of predicted de novo insertion and/or deletion (indel) mutations with a 95% validation rate.
摘要
我们介绍了 DeNovoGear 软件，用于分析来自家族性和体细胞组织测序数据的新突变。DeNovoGear 使用基于似然的错误建模来降低外显子组分析中突变发现的假阳性率，并利用片段信息来识别种系突变的亲本来源。我们在人类全基因组测序数据上使用 DeNovoGear 生成了一组具有 95%验证率的新插入和/或缺失（indel）突变的预测。
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