Developing the Apollo software for high-throughput annotation of multiple genomes

开发用于多个基因组高通量注释的 Apollo 软件

基本信息

批准号：
10736567
负责人：
Ian H Holmes
金额：
$ 46.17万
依托单位：
UNIVERSITY OF CALIFORNIA BERKELEY
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-08-01 至 2027-08-31
项目状态：
未结题

项目摘要

Genome sequencing is becoming cheaper and more powerful. However, a bottleneck to scientific progress using these data is the generation of high-quality genome annotations, describing the location and function of the genes in genomic DNA. In the past, these annotations were generated exclusively by professional biocurators, and these biocurators continue to be a critical source of expertise. However, the number of such biocurators is small compared to the amount of genomic DNA that is available. In recent years, professional biocuration has been supplemented by a growing volunteer force of interested biologists, each generally interested in one or two genes of interest. Although genome annotation is often done in bulk using computational tools, there is currently no substitute for a final pass of manual annotation. This is most commonly done using our Apollo software, which allows for live simultaneous collaborative annotation over the web. Our proposal here is to improve Apollo so as to empower both professional biocurators and crowdsourcing volunteers. We will empower professional biocurators by giving them the power tools they need to simultaneously annotate multiple genomes (by exploiting synteny), annotate variants, and annotate the function of genes. We will empower the crowdsourcing volunteers by lowering barriers to entry, making Apollo more usable. For all users we will train machine learning systems to automatically detect common annotation errors and suggest improvements. We will support Apollo users with maintenance, bugfixing, and various feature requests, as well as extensive outreach including outreach to developers.

基因组测序变得越来越便宜，更强大。但是，瓶颈使用这些数据的科学进步是高质量基因组的产生注释，描述基因在基因组DNA中的位置和功能。在过去，这些注释是由专业生物效力师仅生成的，这些生物效力师仍然是专业知识的关键来源。但是，数量与可用的基因组DNA量相比，这种生物效果量很小。在近年来，专业的生物培养已被越来越多的志愿者补充感兴趣的生物学家的力量，每个人通常对一个或两个感兴趣的基因感兴趣。尽管基因组注释通常是使用计算工具批量进行的，但是目前无法替代手动注释的最后通行证。这是最常见的使用我们的Apollo软件完成了，该软件允许同时进行实时协作通过网络注释。我们在这里的建议是改善阿波罗专业的生物效力家和众包志愿者。我们将授权专业人士生物效应者通过给他们同时注释所需的电动工具多个基因组（通过利用同步），注释变体并注释函数基因。我们将通过降低进入壁垒的范围来赋予众包志愿者的能力，使阿波罗更有用。对于所有用户，我们将训练机器学习系统自动检测常见的注释错误并提出改进。我们将支持Apollo用户维护，错误交易和各种功能请求作为广泛的外展活动，包括向开发人员进行宣传。