作者: S. B. Ng , D. A. Nickerson , M. J. Bamshad , J. Shendure
DOI: 10.1093/HMG/DDQ390
关键词: Biology 、 Identification (biology) 、 Genetics 、 Disease 、 Mutation (genetic algorithm) 、 Massive parallel sequencing 、 Computational biology 、 Human genome 、 Linkage (software) 、 Genome 、 Context (language use)
摘要: Massively parallel sequencing has enabled the rapid, systematic identification of variants on a large scale. This has, in turn, accelerated pace gene discovery and disease diagnosis molecular level potential to revolutionize methods particularly for analysis Mendelian disease. Using massively investigators interrogate both context linkage intervals also genome-wide scale, absence information entirely. The primary challenge now is distinguish between background polymorphisms pathogenic mutations. Recently developed strategies rare monogenic disorders have met with some early success. These include filtering causal based frequency function, ranking conservation scores predicted deleteriousness protein structure. Here, we review recent literature use high-throughput sequence data its mutations disorders.