Forked Position Weight Matrix (FPWM)

FPWM builds a graph model of multiple PWMs (or Seq-logos) to have a better representation of the different motif a TF uses when binding in complex with other transcription factors.

Installation

Type the following in R console:

install.packages("devtools")
library("devtools")
devtools::install_github("https://github.com/benoukraflab/forkedTF")

Dependencies

TFregulomeR (>= 1.2)
ggplot2 (>= 3.2.1)
gridExtra (>= 2.3)
gridGraphics (>= 0.4.1)
ggseqlogo (>= 0.1)
cowplot (>= 1.0.0)
grid (>= 3.6.1)

Documentation

For an extended view of the options please visit the documentation in our vignette

Quick usage

MiniCofactor Report

This function helps in the exploration of binding partners in a cell line. Input the mainTF, cell line of interest and the cobinding_threshold to generate a PDF report of the binding partners.

<<<<<<< HEAD
library("forkedTF")
miniCofactorReport( TF = "CEBPB", cell = "K562",cobinding_threshold=.06)
=======
library("FPWM")
miniCofactorReport( TF = "CEBPB", cell = "K562", cobinding_threshold=.06)
>>>>>>> 3cbca18559f9e1e47d4038b8a0bfde0d610cea27

FPWM creation and plot

Use the createFPWM function to extract the motif, from empirical datasets, that a TF uses when binding with a partner TF. plotFPWM helps in visualizing the FPWM.

fpwm <- createFPWM(mainTF ="CEBPB",
                        partners = c("ATF4","ATF7","ATF3","JUND","FOS","CEBPD"),
                        cell = "K562", 
                        forkPosition = 5,
                        flipMatrix = FALSE)

plotFPWM(fpwm,pdfName="fpwm_plot.pdf")

Writing FPWM

Save the FPWM to a local file can be used in matrix scanning or matrix clustering in transfact format or FPWMtransfact format. Transfact format will have a matrix for each interacting partner in the FPWM, while FPWMtransfact will output a single matrix.

write.FPWM(FPWM = fpwm, format = "transfac", fileName = "FPWM.transfact" )
write.FPWM(FPWM = fpwm, format = "FPWMtransfac", fileName = "FPWM.FPWMtransfac" )

rtmag/FPWM