Robust Software Tools for Variant Identification and Functional Assessment

描述(申请人提供)：基因组测序技术和产量的快速进步为科学家提供了对单个基因组的越来越详细的看法，进一步加深了我们对广泛生物体的遗传变异、人类种群历史以及孟德尔疾病和复杂特征的生物学的理解。直到最近还被限制在非常大的基因组中心的实验，比如人类基因组的重新测序，现在可以由广泛的研究人员进行。虽然这些技术进步将使人类和模型生物遗传学方面的许多新发现成为可能，但它们也带来了巨大的计算挑战。RFA-HG-10-018题为“高通量序列数据分析的信息学工具”，旨在资助现有软件的进一步开发，以确保任何生物或生物医学研究实验室都能从测序技术的进步中受益。我们已经开发了专门的、最先进的工具来处理和分析下一代序列数据。我们的工具包括序列数据分析中的许多关键步骤，从质量控制到阅读图谱，到许多类别的序列变异的鉴定、基因分型和注释，再到寻求将已识别的变异与生物表型联系起来的下游关联分析。这些工具已被用于支持对几个大型、具有挑战性的数据集的分析，这些数据集不仅包括来自1000基因组计划的数据，还包括医学测序项目中测序的&gt；1000全基因组和&gt；2500外显子基因组。在这里，我们建议将这些工具开发成易于使用、便携、文档齐全的包和完整的管道，以促进在各种环境下的生物医学研究。该提案的一个关键组成部分是在银河云中部署这些工具，调查人员无需直接访问当地的高吞吐量计算和数据存储设施即可访问这些工具。

DESCRIPTION (provided by applicant): Rapid advances in genome sequencing techniques and throughput are providing scientists with increasingly detailed views of individual genomes, furthering our understanding of genetic variation in a wide array of organisms, of human population history and of the biology of Mendelian disorders and complex traits. Experiments that were until recently restricted to very large genome centers, such as the resequencing of human genomes, can now be carried out by a wide range of investigators. While these technological advances will enable many new discoveries in human and model organism genetics, they also pose formidable computational challenges. RFA-HG-10-018, entitled "Informatics Tools for High-Throughput Sequence Data Analysis", is intended to fund further development of existing software to ensure that any biological or biomedical research laboratory can benefit from advances in sequencing technologies. We have developed specialized, state-of-the-art tools for the processing and analysis of next generation sequence data. Our tools encompass many key steps in sequence data analysis, ranging from quality control, to read mapping, to the identification, genotyping and annotation of many classes of sequence variation, to downstream association analyses that seek to connect identified variants with organismal phenotypes. These tools have been used to support analysis of several large, challenging datasets including not only data from the 1000 Genomes Project but also >1000 whole genomes and >2500 exomes sequenced in medical sequencing projects. Here, we propose to develop these tools into easy-to-use, portable, well-documented packages and complete pipelines that facilitate biomedical research in a wide variety of settings. A key component of the proposal is the deployment of these tools in the Galaxy cloud, where they will be accessible to investigators without direct access to a local high-throughput computing and data storage facility.