Enabling personal genomics: discovering and understanding genetic variation

高通量测序（HTS）技术，如Illumina/Solexa和AB SOLiD，能够每周测序一个完整的人类基因组，成本比以前的方法低200倍。由此产生的数据由基因组中未知位置的片段组成，长度约为35-120个核苷酸。对这些数据集的分析提出了一个前所未有的信息学挑战，一方面是因为HTS机器单次运行可以产生大量的读取，另一方面是因为读取比以前可用的要短得多。在过去的几年里，短读数据集的分析方法已经开始变得可用，虽然一些问题已经接近用科学界免费提供的可靠工具来解决，但仍然存在许多挑战。在此提案下，我计划开发分析HTS数据的方法，以发现和理解基因组变异，并将这些方法应用于Ciona savignyi模式生物的研究。

High-throughput sequencing (HTS) technologies, such as Illumina/Solexa and AB SOLiD, are able to sequence a full human genome per week at a cost 200-fold less than previous methods. The resulting data consist of pieces - reads - about 35-120 nucleotides long, from unknown locations in the genome. Analysis of these datasets poses an unprecedented informatics challenge, both because of the sheer number of reads that a single run of an HTS machine can produce, and because the reads are significantly shorter than previously available. Methods for the analysis of short-read datasets have started to become available over the last few years, and while some of the problems are close to being solved with reliable tools freely available to the scientific community, there are still many challenges remaining. Under this proposal I plan to develop methodologies to analyze HTS data in order to discover and understand genomic variants, and to apply these methods towards the study of the Ciona savignyi model organism.