Gavin A J, Scheetz T E, Roberts C A, O'Leary B, Braun T A, Sheffield V C, Soares M B, Robinson J P, Casavant T L
Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, USA.
Bioinformatics. 2002 Sep;18(9):1162-6. doi: 10.1093/bioinformatics/18.9.1162.
In gene discovery projects based on EST sequencing, effective post-sequencing identification methods are important in determining tissue sources of ESTs within pooled cDNA libraries. In the past, such identification efforts have been characterized by higher than necessary failure rates due to the presence of errors within the subsequence containing the oligo tag intended to define the tissue source for each EST.
A large-scale EST-based gene discovery program at The University of Iowa has led to the creation of a unique software method named UITagCreator usable in the creation of large sets of synthetic tissue identification tags. The identification tags provide error detection and correction capability and, in conjunction with automated annotation software, result in a substantial improvement in the accurate identification of the tissue source in the presence of sequencing and base-calling errors. These identification rates are favorable, relative to past paradigms.
The UITagCreator source code and installation instructions, along with detection software usable in concert with created tag sets, is freely available at http://genome.uiowa.edu/pubsoft/software.html
在基于EST测序的基因发现项目中，有效的测序后识别方法对于确定混合cDNA文库中EST的组织来源至关重要。过去，由于包含用于定义每个EST组织来源的寡核苷酸标签的子序列中存在错误，此类识别工作的失败率高于必要水平。
爱荷华大学的一个基于大规模EST的基因发现项目催生了一种名为UITagCreator的独特软件方法，可用于创建大量合成组织识别标签。这些识别标签具有错误检测和纠正能力，并且与自动注释软件一起，在存在测序和碱基识别错误的情况下，可大幅提高组织来源的准确识别率。相对于过去的模式，这些识别率是令人满意的。
UITagCreator的源代码和安装说明，以及可与创建的标签集协同使用的检测软件，可在http://genome.uiowa.edu/pubsoft/software.html上免费获取。
