<br>TFTenricher：转录因子靶基因注释富集分析的python工具箱,BMC Bioinformatics

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TFTenricher：转录因子靶基因注释富集分析的python工具箱
BMC Bioinformatics ( IF 2.9 ) Pub Date : 2021-09-16 , DOI: 10.1186/s12859-021-04357-4
Rasmus Magnusson ₁ , Zelmina Lubovac-Pilav ₁

Affiliation

转录因子（TF）是协调基因表达的上游调节因子，因此是生物信息学研究的核心。虽然理解基因和蛋白质生物学背景的核心策略包括注释富集分析，例如基因本体术语富集，但这些方法不太适合分析 TF 组。这是特别正确的，因为此类方法并不旨在包括下游过程，并且给定一组 TF，预期的顶级本体将围绕转录过程。我们推出了 TFTenricher，这是一个 Python 工具箱，专门用于识别基因本体术语、细胞通路以及在用户定义的人类 TF 集下游基因中过度代表的疾病。我们评估了下游基因靶标相对于假阳性注释的推断，并发现了基于共表达的推断，可以最好地预测下游过程。基于这些下游基因，TFTenricher 使用一些最常见的基因功能数据库（包括 GO、KEGG 和 Reactome）来计算功能富集。通过将 TFTenricher 应用到 21 种疾病中 TF 的差异表达，我们发现了与疾病机制相关的重要术语，而对同一数据集的基因集富集分析主要识别了与转录相关的过程。 TFTenricher 包使用户能够搜索任何 TF 组及其下游基因中的生物背景。 TFTenricher 可作为 Python 3 工具箱在 https://github.com/rasma774/Tftenricher 上使用，并遵循 GNU GPL 许可证且具有最少的依赖性。

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TFTenricher: a python toolbox for annotation enrichment analysis of transcription factor target genes

Transcription factors (TFs) are the upstream regulators that orchestrate gene expression, and therefore a centrepiece in bioinformatics studies. While a core strategy to understand the biological context of genes and proteins includes annotation enrichment analysis, such as Gene Ontology term enrichment, these methods are not well suited for analysing groups of TFs. This is particularly true since such methods do not aim to include downstream processes, and given a set of TFs, the expected top ontologies would revolve around transcription processes. We present the TFTenricher, a Python toolbox that focuses specifically at identifying gene ontology terms, cellular pathways, and diseases that are over-represented among genes downstream of user-defined sets of human TFs. We evaluated the inference of downstream gene targets with respect to false positive annotations, and found an inference based on co-expression to best predict downstream processes. Based on these downstream genes, the TFTenricher uses some of the most common databases for gene functionalities, including GO, KEGG and Reactome, to calculate functional enrichments. By applying the TFTenricher to differential expression of TFs in 21 diseases, we found significant terms associated with disease mechanism, while the gene set enrichment analysis on the same dataset predominantly identified processes related to transcription. The TFTenricher package enables users to search for biological context in any set of TFs and their downstream genes. The TFTenricher is available as a Python 3 toolbox at https://github.com/rasma774/Tftenricher , under a GNU GPL license and with minimal dependencies.

更新日期：2021-09-16

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