dba.plotMA {DiffBind} | R Documentation |
Generates MA and scatter plots of differential binding analysis results.
dba.plotMA(DBA, contrast=1, method=DBA$config$AnalysisMethod, th=DBA$config$th, bUsePval=DBA$config$bUsePval, fold=0, bNormalized=TRUE, factor="", bFlip=FALSE, bXY=FALSE, dotSize=.45, bSignificant=TRUE, bSmooth=TRUE, bLoess=TRUE, xrange, yrange, ...)
DBA |
DBA object, on which |
contrast |
number of contrast to report on.
See Alternatively, an MA plot can be generated without a specific contrast,
plotting one set of samples against another.
In this case, |
method |
method or vector of methods to plot results for: |
th |
significance threshold; all sites with FDR (or p-values, see |
bUsePval |
logical indicating whether to use FDR ( |
fold |
will only include sites with fold change greater than this as significant (colored red). |
bNormalized |
logical indicating whether to plot normalized data using normalization factors
computed by differential analysis method ( |
factor |
string to be prepended to plot main title; e.g. factor name. |
bFlip |
logical indicating that order of groups in contrast should be "flipped", allowing control of which sample group will have positive and which will have negative fold changes. |
bXY |
logical indicating whether to draw MA plot ( |
dotSize |
size of points on plot ( |
bSignificant |
Logical indicating if points corresponding to significantly
differentially bound sites (based on |
bSmooth |
logical indicating that basic plot should be plotted using
|
bLoess |
logical indicating that a MA plot should include a fitted loess curve. |
xrange |
vector of length 2 containing the desired minimum and maximum concentrations to plot. |
yrange |
vector of length 2 containing the desired minimum and maximum fold changes to plot. |
... |
passed to underlying plotting functions. |
Rory Stark
data(tamoxifen_analysis) # default MA plot dba.plotMA(tamoxifen) # Show different normalizations tamoxifen <- dba.normalize(tamoxifen,method=DBA_ALL_METHODS, library=DBA_LIBSIZE_PEAKREADS, background=FALSE) tamoxifen <- dba.analyze(tamoxifen, method=DBA_ALL_METHODS) par(mfrow=c(3,2)) dba.plotMA(tamoxifen,th=0,bNormalized=FALSE,sub="NON-NORMALIZED") dba.plotMA(tamoxifen,th=0,bNormalized=FALSE,sub="NON-NORMALIZED") dba.plotMA(tamoxifen,method=DBA_DESEQ2,bNormalized=TRUE, sub="DESeq2_RLE-RiP") dba.plotMA(tamoxifen,method=DBA_EDGER,bNormalized=TRUE, sub="edgeR_TMM-RiP") tamoxifen <- dba.normalize(tamoxifen, method=DBA_ALL_METHODS, normalize=DBA_NORM_LIB, background=FALSE) tamoxifen <- dba.analyze(tamoxifen,method=DBA_ALL_METHODS) dba.plotMA(tamoxifen,method=DBA_DESEQ2,bNormalized=TRUE, sub="DESeq2_LIB-FULL") dba.plotMA(tamoxifen,method=DBA_EDGER,bNormalized=TRUE, sub="edgeR_LIB-FULL") # MA plots of samples without a contrast data(tamoxifen_counts) par(mfrow=c(2,2)) dba.plotMA(tamoxifen,list(Resistant=tamoxifen$masks$Resistant, Responsive=tamoxifen$masks$Responsive), bNormalized=FALSE) dba.plotMA(tamoxifen,list(MCF7=tamoxifen$masks$MCF7), bNormalized=FALSE) dba.plotMA(tamoxifen, list(Sample1=1), bNormalized=FALSE) dba.plotMA(tamoxifen, list(Random=sample(1:11,5)), bNormalized=FALSE) #XY plots (with raw and normalized data) data(tamoxifen_analysis) par(mfrow=c(1,2)) dba.plotMA(tamoxifen,bXY=TRUE,bSmooth=FALSE,bNormalized=FALSE, sub="NON_NORMALIZED") dba.plotMA(tamoxifen,bXY=TRUE,bSmooth=FALSE,bNormalized=TRUE, sub="DESeq2-RLE-Background")