BioConductor packages for R
PWMEnrich - Asses the enrichment of already known PWMs (e.g. from JASPAR) in DNA sequences. Motif hits in a sequence or DNA region are considered together and P-values derived for their joint pattern. The package implements multiple algorithms, including fixed-threshold (Z-score) and threshold-free (Lognormal normalization and Clover) methods. The main goal is to identify a set of transcription factors that most likely bind to a single sequence, group of sequences, or show significantly different binding affinity between two sets of sequences.
ddgraph - Distinguish direct from indirect interactions in gene regulation and infer combinatorial code from highly correlated variables such as transcription factor binding profiles. The package implements the Neighbourhood Consistent PC algorithm (NCPC) and draws Direct Dependence Graphs to represent dependence structure around a target variable. The package also provides a unified interface to other Graphical Modelling (Bayesian Network) packages for distinguishing direct and indirect interactions.
Publication: A graphical modelling approach to the dissection of highly correlated transcription factor binding site profiles. Stojnic et al. PLoS Computational Biology, 8(11):e1002725, 2012, doi: 10.1371/journal.pcbi.1002725.
Gene Regulation in Prokaryotes (GRiP)
Description: GRiP is an agent based model of the transcription factors (TFs) search process for their target sites, which is written in Java 1.6. The software represents the DNA sequence, TFs and the interaction between TFs and the DNA (facilitated diffusion mechanism), or between various TFs (cooperative behaviour). The software will output both information on the dynamics associated with the search process (locations of molecules) and also steady state results (affinity landscape, occupancy-bias, collision hotspots, search times, the times the target sites were occupied and statistics about the 1D random walk process).
Publication: GRiP: a computational tool to simulate transcription factor binding in prokaryotes. Nicolae Radu Zabet and Boris Adryan. Bioinformatics, 28 (9): 1287-1289, 2012, doi:10.1093/bioinformatics/bts132.
FlyTF Drosophila Transcription Factor Database
Description: The detailed annotation of transcription factors is outside the scope of a general database like FlyBase. We have curated a list of site-specific transcription factors that are encoded in the Drosophila genome and made these annotations available through an InterMine-based web interface. FlyTF has emerged to a defacto standard in many bioinformatics studies.
Publication: FlyTF: improved annotation and enhanced functionality of the Drosophila transcription factor database. Pfreund et al. Nucleic Acids Research, 38(Database issue):D443-7, 2010, doi:10.1093/nar/gkp910.