Liu Chuan-Kun, Chen Yan-Hau, Tang Cheng-Yang, Chang Shu-Chuan, Lin Yi-Jung, Tsai Ming-Fang, Chen Yuan-Tsong, Yao Adam
National Genotyping Center, Academia Sinica, Taipei, Taiwan 11529, R.O.C.
BMC Bioinformatics. 2008 Dec 12;9 Suppl 12(Suppl 12):S10. doi: 10.1186/1471-2105-9-S12-S10.
With the flood of information generated by the new generation of sequencing technologies, more efficient bioinformatics tools are needed for in-depth impact analysis of novel genomic variations. FANS (Functional Analysis of Novel SNPs) was developed to streamline comprehensive but tedious functional analysis steps into a few clicks and to offer a carefully designed presentation of results so researchers can focus more on thinking instead of typing and calculating.
FANS http://fans.ngc.sinica.edu.tw/ harnesses the power of public information databases and powerful tools from six well established websites to enhance the efficiency of analysis of novel variations. FANS can process any point change in any coding region or GT-AG splice site to provide a clear picture of the disease risk of a prioritized variation by classifying splicing and functional alterations into one of nine risk subtypes with five risk levels.
FANS significantly simplifies the analysis operations to a four-step procedure while still covering all major areas of interest to researchers. FANS offers a convenient way to prioritize the variations and select the ones with most functional impact for validation. Additionally, the program offers a distinct improvement in efficiency over manual operations in our benchmark test.
随着新一代测序技术产生的信息大量涌现，需要更高效的生物信息学工具来对新的基因组变异进行深入的影响分析。FANS（新型单核苷酸多态性功能分析）的开发旨在将全面但繁琐的功能分析步骤简化为只需点击几下，并提供精心设计的结果呈现方式，以便研究人员能够更多地专注于思考而非打字和计算。
FANS显著简化了分析操作，将其简化为一个四步流程，同时仍涵盖研究人员感兴趣的所有主要领域。FANS提供了一种方便的方法来对变异进行优先级排序，并选择具有最大功能影响的变异进行验证。此外，在我们的基准测试中，该程序在效率方面比手动操作有了明显提高。
