期刊
GENOME RESEARCH
卷 17, 期 5, 页码 659-666出版社
COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT
DOI: 10.1101/gr.6151507
关键词
-
资金
- NCI NIH HHS [P01 CA101937] Funding Source: Medline
- NHGRI NIH HHS [U54 HG003079, HG003079] Funding Source: Medline
Small insertions and deletions (indels) and single nucleotide polymorphisms (SNPs) are common genetic variants that are thought to be associated with a wide variety of human diseases. Owing to the genome's size and complexity, manually characterizing each one of these variations in an individual is not practical. While significant progress has been made in automated single-base mutation discovery from the sequences of diploid PCR products, automated and reliable detection of indels continues to pose difficult challenges. In this paper, we present PolyScan, an algorithm and software implementation designed to provide de novo heterozygous indel detection and improved SNP identification in the context of high-throughput medical resequencing. Tests on a human diploid PCR-based sequence data set, consisting of 90,270 traces from 13 genes, indicate that PolyScan identified similar to 90% of the 151 consensus indel sites and similar to 84% of the 1546 heterozygous indels previously identified by manual inspection. Tests on tumor-derived data show that PolyScan better identifies high-quality, low-level mutations as compared with other mutation detection software. Moreover, SNP identification improves when reprocessing the results of other programs. These results suggest that PolyScan may play a useful role in the post human genome project research era.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据