Center for Systems Genomics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, Eberly College of Science, The Huck Institutes of the Life Sciences, University Park, Pennsylvania, PA, USA.
BioData Min. 2013 Dec 30;6(1):25. doi: 10.1186/1756-0381-6-25.
The ever-growing wealth of biological information available through multiple comprehensive database repositories can be leveraged for advanced analysis of data. We have now extensively revised and updated the multi-purpose software tool Biofilter that allows researchers to annotate and/or filter data as well as generate gene-gene interaction models based on existing biological knowledge. Biofilter now has the Library of Knowledge Integration (LOKI), for accessing and integrating existing comprehensive database information, including more flexibility for how ambiguity of gene identifiers are handled. We have also updated the way importance scores for interaction models are generated. In addition, Biofilter 2.0 now works with a range of types and formats of data, including single nucleotide polymorphism (SNP) identifiers, rare variant identifiers, base pair positions, gene symbols, genetic regions, and copy number variant (CNV) location information.
Biofilter provides a convenient single interface for accessing multiple publicly available human genetic data sources that have been compiled in the supporting database of LOKI. Information within LOKI includes genomic locations of SNPs and genes, as well as known relationships among genes and proteins such as interaction pairs, pathways and ontological categories.Via Biofilter 2.0 researchers can:• Annotate genomic location or region based data, such as results from association studies, or CNV analyses, with relevant biological knowledge for deeper interpretation• Filter genomic location or region based data on biological criteria, such as filtering a series SNPs to retain only SNPs present in specific genes within specific pathways of interest• Generate Predictive Models for gene-gene, SNP-SNP, or CNV-CNV interactions based on biological information, with priority for models to be tested based on biological relevance, thus narrowing the search space and reducing multiple hypothesis-testing.
Biofilter is a software tool that provides a flexible way to use the ever-expanding expert biological knowledge that exists to direct filtering, annotation, and complex predictive model development for elucidating the etiology of complex phenotypic outcomes.
通过多个综合数据库资源库提供的日益增长的生物信息财富可以用于对数据进行高级分析。我们现在已经广泛修订和更新了多用途软件工具 Biofilter，该工具允许研究人员根据现有生物学知识对数据进行注释和/或过滤，以及生成基因-基因相互作用模型。Biofilter 现在有了 Knowledge Integration Library（LOKI），用于访问和整合现有的综合数据库信息，包括更灵活地处理基因标识符的歧义。我们还更新了生成交互模型重要性得分的方式。此外，Biofilter 2.0 现在可以处理各种类型和格式的数据，包括单核苷酸多态性 (SNP) 标识符、罕见变异标识符、碱基对位置、基因符号、遗传区域和拷贝数变异 (CNV) 位置信息。
Biofilter 提供了一个方便的单一接口，用于访问已在 LOKI 支持数据库中编译的多个公开可用的人类遗传数据源。LOKI 中的信息包括 SNPs 和基因的基因组位置，以及基因和蛋白质之间的已知关系，如相互作用对、途径和本体类别。通过 Biofilter 2.0，研究人员可以：
注释基于基因组位置或区域的数据，例如关联研究或 CNV 分析的结果，并用相关的生物学知识进行更深入的解释；
根据生物学标准过滤基于基因组位置或区域的数据，例如过滤一系列 SNPs，仅保留特定基因中特定感兴趣途径中的 SNPs；
根据生物学信息生成基因-基因、SNP-SNP 或 CNV-CNV 相互作用的预测模型，优先考虑基于生物学相关性进行测试的模型，从而缩小搜索空间并减少多重假设检验。
Biofilter 是一种软件工具，它提供了一种灵活的方法，可以利用现有的不断扩展的专家生物学知识来指导过滤、注释和复杂预测模型的开发，以阐明复杂表型结果的病因。
