Regulatory Snapshots is a method to identify regulatory modules composed of genes exhibiting coherent transcriptional activity in a specific time interval and their transcription factors.
Regulatory Snapshots is described in the following article:
Gonçalves JP, Aires RS, Francisco AP, and Madeira SC. Regulatory Snapshots: Integrative Mining of Regulatory Modules from Expression Time Series and Regulatory Networks, PLoS ONE 2012, 7(5):e35977.
[full text html] [full text pdf] [cite it] doi:10.1371/journal.pone.0035977
Regulatory modules are discovered in two steps:
- Identification of temporal transcriptional modules: time-aware biclustering step to uncover subsets of genes with coherent behavior spanning a subset of consecutive time points;
- Prioritization of transcription factors targeting the modules at each time point: personalized ranking on the transpose of the regulatory network graph taking as input signal the expression level of the genes in each transcriptional module at each time point.
Visual representations, called regulatory snapshots after the method's name, are also depicted for each regulatory module, containing the transcriptionally coherent genes and their most relevant transcription factors at each time point. Regulatory Snapshots expose the evolution of the regulatory activity in the module over time.
In one of the case studies, we used Regulatory Snapshots to unravel and characterize regulatory modules underlying Saccharomyces cerevisiae's response to heat shock. Results can be easily reproduced using our software tools BiGGEsTS and Regulatory Snapshots as described in the tutorial section.
Regulatory Snapshots is a modular framework, which allows the researcher to replace the transcriptional module identification or the transcription factor discovery by other methods if he/she wishes to do so. If you're interested in following our approach, please consider using our tools:
- For a first step of time-aware biclustering: BiGGEsTS, a standalone tool for the identification of transcriptional modules (biclusters) in time series gene expression data. Some features:
- Methods for preprocessing time series expression data (filtering and filling of missing values, normalization, smoothing, discretization).
- Time-aware biclustering algorithms for discovering transcriptional modules.
- Post-processing options for filtering and sorting biclusters.
- Overrepresentation of GO terms: statistical enrichment of Gene Ontology (GO) terms annotated with the genes in the biclusters
- Visual exploration of the data, including heatmaps, expression profile charts, ontology graphs of significant GO terms.
- Bicluster(s) export to the input format for the Regulatory Snapshots tool.
- For the second step of transcription factor prioritization: Regulatory Snapshots, a web application for the prioritization of transcription factors targeting a subset of genes over time based on their expression values at consecutive time points. Currently available for Saccharomyces cerevisiae only, using regulatory data from YEASTRACT. Some features:
- Straightforward input of a group of genes of interest and their expression for one or more time points.
- Identify and generate a visual representation of the most relevant regulators targeting the genes in the group.
- Interactive figures, where a particular TF or target can be hovered over or selected in order to highlight the regulations in which it is involved. Multiple selection is allowed.
- Browsing of the figures obtained for the several time points.
- Try it! Go to Regulatory Snapshots, press "SAMPLE" and then "RANK".