- Link to data compendium hosted in Singapore and Canada;
- Link to TF motifs and DNA methylation in human and mouse;
- Perform TF interactome analysis coupled with DNA methylation and other chromatin signals such as chromatin accessibility.
TFregulomeR comprises of a comprehensive compendium of transcription factor binding sites (TFBSs) derived from the MethMotif and GTRD, as well as the ready-to-use functionality in R language facilitating data access, integration and analysis. The binding motifs predicted in-silico from MethMotif and GTRD describe cell specific transcription factor (TF) binding propensities, while the DNA methylation profiles from MethMotif portray a second epigenetic dimension in TF binding events. The whole toolbox allows a better understanding of the TF binding propensities in a cell-specific manner.
This repository is TFregulomeR stable release
Current TFregulomeR stable version: 2.0.0 (Updated on 5 March 2020).
You can check detailed package instructions in Vignettes
Current Functionalities v2.0.0
here for functionality update notesClick
Currently, TFregulomeR links to data compendium hosted in Singapore (default) and Canada. User is able to switch the servers by changing the input parameter 'server' when using those functions highlighted as 'multi-servers' below. For Singapore server, please use
server='sg', and for Canada one, please use
server='ca'. For example, when browsing TFregulomeR data compendium hosted in Canada, using
dataBrowser(server='ca'). For details, please refer to the Vignettes.
Note: new function is highlighted in bold font.
- Browse the TFregulomeR data compendium (dataBrowser(), multi-servers)
- Load TF peaks (loadPeaks(), multi-servers)
- Search motif matrix and DNA methylation score matrix (searchMotif(), multi-servers)
- Plot motif or MethMotif logo (plotLogo)
- Export motif matrix and DNA methylation score matrix (exportMMPFM)
- Get context-independent peaks along with DNA methylation profiles (commonPeaks(), multi-servers, & commonPeakResult())
- Get context-dependent peaks along with DNA methylation profiles (exclusivePeaks(), multi-servers, & exclusivePeakResult())
- Form a intersected matrix between two lists of peak sets along with DNA methylation profiles, read enrichments and users' input external signals, for interactome and co-binding partner studies (intersectPeakMatrix(), multi-servers, & intersectPeakMatrixResult()). - NEW Feature
- Automatically generate a PDF report for TF co-factors along with motif sequences, DNA methylation (within motif and in 200bp regions) and read enrichments (cofactorReport()).
- Automatically produce a dynamic three-dimensional interface showing TF interactome coupled with DNA methylation and/or users’ input external signal values (interactome3D()). - NEW Function
- Plot the TFBS distribution in a given list of peak sets (motifDistrib(), multi-servers, & plotDistrib()).
- Annotate peak genomic locations (genomeAnnotate(), multi-servers).
- Annotate ontologies of target genes by a peak set (greatAnnotate()).
- Convert a motif matrix to a PFMatrix calss object for TFBSTools package (toTFBSTools(), multi-servers).
Current TFBSs in TFregulomeR compendium
here for TFregulomeR compendium update notesClick
TFregulomeR data compendium version: 2.0.0
|PWM with DNA methylation records||679|
|Species||human (hg38) and mouse (mm10)|
|Organ||brain, stem_cell, blood_and_lymph, connective_tissue, liver, colorectum, muscle, bone, stomach, prostate, pancreas, skin, eye, breast, intestine, kidney, lung, esophagus, heart, testis, uterus, spleen, limb, body, cervix, placenta, undefined, adrenal_gland, neck_and_mouth, head, ovary, pleura, thymus, fallopian, vagina|
|Sample type||primary_cells, cell_line, tissue|
|Cell or tissue||721|
|Disease state||normal, tumor, Simpson_Golabi_Behmel_syndrome, progeria, metaplasia, unknown, immortalized, premetastatic|
Quy Xiao Xuan Lin, Denis Thieffry, Sudhakar Jha, Touati Benoukraf. (2019) TFregulomeR reveals transcription factors’ context-specific features and functions. Nucleic Acids Res., 10.1093/nar/gkz1088. [Manuscript]
The scripts of case studies used in our manuscript are available as below.
Required packages: the packages below are the basic prerequisite packages for TFregulomeR functionalities
Optional packages: the packages below are optional since they are required only in some functions or some options in a function
- rGREAT (>= 1.16.1): only requried in
- rbokeh (>= 0.5.0): only required when users opt to export an intuitive HTML report in
- TxDb.Hsapiens.UCSC.hg38.knownGene (>= 3.4.0): only required when users opt to annotate hg38 peak locations in
- TxDb.Hsapiens.UCSC.hg19.knownGene (>= 3.2.2): only required when users opt to annotate hg19 peak locations in
- TxDb.Mmusculus.UCSC.mm10.knownGene (>= 3.4.4): only required when users opt to annotate mm10 peak locations in
- TxDb.Mmusculus.UCSC.mm9.knownGene (>= 3.2.2): only required when users opt to annotate mm9 peak locations in
- TFBSTools (>= 1.20.0): only required in
- rGREAT (>= 1.16.1): only requried in
In R console,
# if you have not installed "devtools" package install.packages("devtools") devtools::install_github("benoukraflab/TFregulomeR")
The step above will automatically install the required packages. However, you still need to install optional packages if you opt to use the functions such as
GNU General Public License v3.0