ProbFAST: Probabilistic functional analysis system tool

Abstract

Background: The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis.

Results: We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes.

Conclusions: ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast.

Figure 1

Screenshot of ProbFAST input data page. To add a new analysis, the user must add the project name and set up the pre processing information (optional). Next, the user must choose organism, platform and loading gene expression sample from GEO and/or upload the data.

Figure 2

Creating question. Now, the user needs to specify one or more target question. For that, work layer allows choosing sample and question operators to help creating the question. Double click on the sample name allows set pool analysis.

Figure 3

Gene search. Firstly, users can select the question target and cutoff value through the Gene Search panel. Then the genes associated question and cutoff will be showed. By clicking on any image from functional categories it enables the user to visualize indexed information on the layer in the right side. Key-word filters can be applied in order to refine results.

Figure 4

Enrichment analysis. An example of the enriched functional term list output for KEGG category. The resulting enriched KEGG pathways can be visualized using a table consisting of enrichment cutoff values of the enriched terms (with web links to additional information), total of the relevant annotated genes and counting of transcripts.

Figure 5

Functional Screening. The functional categories presenting the largest number of genes with values above the cutoff related to the question will be listed here.