MotIV (version 1.28.0)

plot-methods: Plot Motiv

Description

This functions are used to vizualise and validate motiv analysis.

Usage

"plot"(x, y=NULL, main=NULL, sub=NULL, ncol=0, nrow=0, top=3, bysim=TRUE, rev=FALSE, trim=0.05, cex)
	
	"plot"(x, y, sort=FALSE, group=FALSE, main=NULL, sub=NULL, ncol=0, nrow=0, xlim=NULL, correction=TRUE,  bysim=TRUE, strand=FALSE, type="distribution", trim=0.05, col=c("blue", "red"), border=c("black", "black"), lwd=2, lty=1, nclass=20, bw="nrd0", cex=1, vcol=c("red", "green"))

Arguments

x

An object of class motiv.

y

The GADEM type object associated with the motiv object.

ncol, nrow

A numeric value giving the the number of columns and rows to plot.

top

A numeric value giving the number of best matches per motif to display.

rev

A logical value. If TRUE, print reverse motif for negatif strand.

main

An overall title for the plot: see title.

sub

A sub title for the plot: see 'title'

type

What type of plot should be drawn. Possible values are : distribution to display the binding sites distribution within the peaks or distance to show the pairwise distance between motifs.

strand

If TRUE, distribution will be plot for both forward and reverse strand.

group

If TRUE, similar motifs will be grouped.

sort

If TRUE, motifs will be plot according their computed variance.

bysim

If TRUE, the 'similar' field (defined with the combine function) will be print instead of the original name.

xlim

A numeric vectors of length 2, giving the x coordinates ranges.

correction

If TRUE, corrects the position according to the alignment.

trim

A numeric value. Define the mimimun information content value for which the logo letters are shown.

col, border, lwd, lty

Define respectively the color, the border, the line wide and the line type of both curve and histogram. See 'par'.

nclass

A numerical value giving the number of class for the histogram.

bw

he smoothing bandwidth to be used to calculate the density. See density.

cex, vcol

A numerical value giving the amount by which plotting text should be magnified relative to the default.

Details

A single motiv object (usualy provied by motifMatch) will plot the list of identified transcription factors for each motif. With rev=TRUE, the transcription factor logo will be print to correspond to the real alignment instead of original TF PWM. Giving a motiv object and a gadem object with type="distribution" will show the motif repartition within gadem peaks. If strand=TRUE, a distinct distribution is made for forward and reverse strand.

A var.test is automatically made to help to distinguish centered distribution. The distribution with lowest variance is assign as "reference" distribution to compute the var.test statistic. With sort=TRUE, distribution are plot according decreasing statistic.

type="distance" indicates to compute and plot the distance between each pair of motif. It aslo provied Venn diagramm that returns the proportion of common sequences per pair of motif.

The group argument indicates to consider similar motif as a single motif. With correction=TRUE the motif position is corrected accoring to the alignment. It means that the gap/"N" contained in the alignments are removed to give a corrected start and end position.

Examples

#####Database and Scores#####
path <- system.file(package="MotIV")
jaspar <- readPWMfile(paste(path,"/extdata/jaspar2010.txt",sep=""))
jaspar.scores <- readDBScores(paste(path,"/extdata/jaspar2010_PCC_SWU.scores",sep=""))

#####Input#####
data(FOXA1_rGADEM)
motifs <- getPWM(gadem)
motifs.trimed <- lapply(motifs,trimPWMedge, threshold=1)
#####Analysis#####
foxa1.analysis.jaspar <- motifMatch(inputPWM=motifs,align="SWU",cc="PCC",database=jaspar,DBscores=jaspar.scores,top=5)
summary(foxa1.analysis.jaspar )

#####Filters#####
f.foxa1<-setFilter(name="", tfname="FOXA1", top=3, evalueMax=10^-5)
f.ap1 <- setFilter (tfname="AP1", top=3)
f.foxa1.ap1 <- f.foxa1 | f.ap1 
foxa1.filter <- filter(foxa1.analysis.jaspar, f.foxa1.ap1, exact=FALSE, verbose=TRUE)
foxa1.split <- split(foxa1.analysis.jaspar, c(f.foxa1, f.ap1) , drop=FALSE, exact=FALSE, verbose=TRUE)
foxa1.filter.combine <- combineMotifs(foxa1.filter, c(f.foxa1, f.ap1), exact=FALSE, name=c("FOXA1", "AP1"), verbose=TRUE)

#####Plots#####
plot(foxa1.filter.combine, ncol=2,top=5, rev=FALSE, main="FOXA", bysim=TRUE)
plot(foxa1.filter.combine ,gadem,ncol=2, type="distribution", correction=TRUE, group=FALSE, bysim=TRUE, strand=FALSE, sort=TRUE, main="FOXA", nclass=20, bw=2)
plot(foxa1.filter.combine ,gadem,type="distance", correction=TRUE, group=TRUE, bysim=TRUE, main="FOXA", strand=FALSE, xlim=c(-100,100), nclass=20, bw=8)