SBIR Phase II: Mathematical Models for DNA Sequencing Quality Control

* 9612376年轻 这个小型企业创新研究第二阶段项目解决了将一致的定量错误率估计与DNA序列数据相关联的问题，并由此改进了对这些数据的质量控制。DNA序列数据在研究、数据库、诊断和治疗生物技术甚至诉讼中的使用越来越多，这要求所使用的数据的质量是可客观评估的。将确定对DNA测序的质量控制重要的变量，例如序列内容和位置的误差依赖性。方法将 开发用于将这种错误率信息包括到现有的和开发中的数据库条目中，并且基于对已知的最佳设计的DNA序列进行测序的结果，为常规地向这种数据库提供DNA序列数据的实验室提供质量控制评分。该项目还将开发协议和方便用户的软件，用于定期评估特定测序仪的当前性能状况。这项调查将基于理论统计分析，计算机模拟，并从测序实验的结果，使用专门设计的，合成的DNA片段。 ***

*** 9612376 Young This Small Business Innovation Research Phase II project addresses the problem of associating consistent, quantitative error rate estimates with DNA sequence data and the resulting improved quality control on such data. The growing use of DNA sequence data in research, databases, diagnostic and therapeutic biotechnology, and even litigation requires that the quality of data being used be objectively assessable. Variables will be identified which are important to quality control of DNA sequencing such as error dependency on sequence content and position. Methods will be developed for including such error rate information into existing and developing database entries and, based on results from sequencing known optimally designed DNA sequences, provide a quality control score for laboratories which routinely contribute DNA sequence data to such databases. The project will also develop protocols and user-friendly software for periodically assessing the current state of performance for given sequencing machines. This investigation will be based on theoretical statistical analyses, computer simulations, and on results from sequencing experiments using specially designed, synthetic DNA fragments. ***