TFAT: Transcription factor analysis through data integration and scalable metrics
TFAT. Transcription Factors. Target genes. Degreeof reliability. Web tool. Enrichment analysis.
Currently there are several tools proposed for analysis of Transcription Factors (TF), such as TFCheckpoint, JASPAR, SSTAR, GTRD, Enrichr. However none of these tools offers a complete experience in which the reliability of TF can be evaluated, that is, if in fact an analyzed protein is a TF and its association with the target gene. Numerous databases were built over time, all of them with very rich information, but the intrinsic complexity of the data, the volume of information, problems of gene nomenclature and several other factors meant that such tools did not offer a complete spectrum of analysis . On the other hand, to work with a large volume of data requires advanced computer skills. However, the general public interested in analyzing this data are professionals from the biological areas. Configuring itself as a barrier, since the academic formation of this area does not offer in its curricular components programming disciplines. Faced with this situation, this work aims to create a web tool exclusively for the analysis of TFs. Containing the integration of different databases and a set of scripts to manipulate this information, along with the crucial parameters defined by the user in its analysis, Transcription Factor Analysis Tools (TFAT) was designed and developed. The core of this tool is the analysis to identify the key TFs in the modularization of gene transcription, that is, the enrichment of the regulatory TFs of a list of genessubmitted by the user, that through the scripts that integrate the same, consult its database, identify the TFs that are associated with the listed genes and calculate the enrichment p-value. In addition, the tool verifies TF reliability, makes available predictions, and converts items from a list to the Entrez Gene's GeneID or Symbol. Anotherfeature of this work is the use of TF reliability applied throughout the tool. This degree of reliability takes into account evidence from different databases, experiments, predictions and other characteristics of TFs. With a standard mode and a user-defined mode, this reliability feature allows for a full customization through filters in the queries and analysis control for the end user.