dba.plotHeatmap: Draw a binding site heatmap
In DiffBind: Differential Binding Analysis of ChIP-Seq Peak Data

Description Usage Arguments Details Value Author(s) See Also Examples

Draws a binding site heatmap

dba.plotHeatmap(DBA, attributes=DBA$attributes, maxSites=1000, minval, maxval,
                contrast, method=DBA$config$AnalysisMethod, 
                th=DBA$config$th, bUsePval=DBA$config$bUsePval, 
                report, score, bLog=TRUE, mask, sites, sortFun=sd,
                correlations=TRUE, olPlot=DBA_COR, 
                ColAttributes,RowAttributes, colSideCols, rowSideCols=colSideCols,
                margin=10, colScheme="Greens", distMethod="pearson",
                ...)

DBA

DBA object.

`attributes`	attribute or vector of attributes to use for column labels: `DBA_ID` `DBA_TISSUE` `DBA_FACTOR` `DBA_CONDITION` `DBA_TREATMENT` `DBA_REPLICATE` `DBA_CONSENSUS` `DBA_CALLER`
`maxSites`	maximum number of binding sites to use in heatmap. Only used when not drawing a correlation heatmap (`correlations=FALSE`)
`minval`	Set all scores less than this to minval
`maxval`	Set all scores greater than this to maxval
`contrast`	number of contrast to report on; if present, draws a heatmap based on a differential binding affinity analysis (see `dba.analyze`). Only significantly differentially bound sites will be used (subject to the `th` and `bUsePval` parameters). If mask is unspecified, only the samples in the contrast will be included. See `dba.show(DBA, bContrast=TRUE)` to get contrast numbers. If missing, uses scores in the main binding matrix.
`method`	analysis method (used in conjunction with contrast): `DBA_DESEQ2` `DBA_DESEQ2_BLOCK` `DBA_EDGER` `DBA_EDGER_BLOCK`
`th`	significance threshold; all sites with FDR (or p-values, see b`UsePval`) less than or equal to this value will be included in the report (subject to `maxSites`). Used in conjunction with `contrast`.
`bUsePval`	logical indicating whether to use FDR (`FALSE`) or p-value (`TRUE`) for thresholding. Used in conjunction with `contrast`.
`report`	report (obtained from `dba.report` specifying the data to be used. If this is present, the `method`, `th`, and `bUsePval` parameters are ignored. Used in conjunction with `contrast`.
`score`	Score to use for count data. Only used when plotting the global binding matrix (no contrast specified). One of: `DBA_SCORE_NORMALIZED` `DBA_SCORE_READS` `DBA_SCORE_CONTROL_READS` `DBA_SCORE_READS_MINUS` `DBA_SCORE_READS_FOLD` `DBA_SCORE_RPKM` `DBA_SCORE_RPKM_FOLD` `DBA_SCORE_RPKM_MINUS`
`bLog`	Logical indicating that log2 values should be used. Only applicable with read count scores (not peak scores).
`mask`	mask indicating a subset of peaksets to use when using global binding matrix scores. If a `contrast` is specified, these peaksets will be included, but only the significantly differentially bound sites (using `th`, `bUsePva`l, and/or `report`) will be included.
`sites`	logical vector indicating which sites to include; first `maxSites` of these. Only relevant when using global binding matrix (`contrast` is missing).
`sortFun`	function taking a vector of scores and returning a single value. Only relevant when using global binding matrix (`contrast` is missing). If not equal to `FALSE`, the global binding matrix will be sorted (descending) on the results, and the first `maxSites` used in the heatmap. Recommended sort function options include `sd`, `mean`, `median`, `min`.
`correlations`	logical indicating that a correlation heatmap should be plotted (`TRUE`). If `FALSE`, a binding heatmap of scores/reads is plotted. This parameter can also be set to a correlation record; see `dba.overlap(mode=DBA_OLAP_ALL)`, in which case a correlation heatmap is plotted based on the specified correlation record, using the statistic specified in `olPlot`.
`olPlot`	if correlations is specified as a dataframe returned by `dba.overlap`, indicates which statistic to plot. One of: `DBA_COR` Correlation `DBA_OLAP` Percentage overlap `DBA_INALL` number of peaks common to both samples
`ColAttributes`	Attribute or vector of attributes to plot for column color bars. If missing, all attributes with two or more unique non-NA values will be plotted. (For correlation heatmaps, `DBA_GROUP` will be plotted in the column color bar by default when a `contrast` is specified). A value of `NULL` indicates that no column color bar should be drawn. Allowable attribute values include: `DBA_GROUP` `DBA_TISSUE` `DBA_FACTOR` `DBA_CONDITION` `DBA_TREATMENT` `DBA_REPLICATE` `DBA_CALLER`
`RowAttributes`	Attribute or vector of attributes for row color bars. Row color bars are only allowed for correlation heatmaps. Same values as for `ColAttributes` parameter. Default is to draw a row color bar only if a `contrast` is specified, in which case the plotted attribute is `DBA_GROUP` (if present).
`rowSideCols`	Vector of colors to use in row color bars. Uses default colors if missing. Can also be a list of color vectors.
`colSideCols`	Vector of colors to use in column color bars. Uses default colors if missing. Can also be a list of color vectors.
`margin`	margin size of plot
`colScheme`	Color scheme; see `colorRampPalette`
`distMethod`	distance method for clustering; see `Dist`
`...`	passed on to `heatmap.2`, e.g. `scale` etc.

MODE: Correlation Heatmap plot using statistics for global binding matrix:

dba.plotHeatmap(DBA, attributes=DBA$attributes, minval, maxval, correlations, olPlot, colScheme="Greens", distMethod="pearson", ...)

MODE: Correlation Heatmap plot using statistics for significantly differentially bound sites:

dba.plotHeatmap(DBA, attributes=DBA$attributes, minval, maxval, contrast, method=DBA_DESEQ2, th=0.05, bUsePval=F, mask, overlaps, olPlot=DBA_COR, colScheme="Greens", distMethod="pearson", ...)

MODE: Binding heatmap plot using significantly differentially bound sites:

dba.plotHeatmap(DBA, attributes, maxSites, minval, maxval, contrast, method, th, bUsePval, correlations=FALSE, colScheme, distMethod, ...)

MODE: Binding heatmap plot using the global binding matrix:

dba.plotHeatmap(DBA, attributes, maxSites, minval, maxval, mask, sites, correlations=FALSE, sortFun, colScheme, distMethod, ...)

if correlations is not FALSE, the overlap/correlation matrix is returned.

if correlations is FALSE, the sites used in the heatmap are returned in a GRanges object, in the row order they appear (top to bottom). The metadata contains a column for each sample (also in the order they are appear in the clustering plot), with the values being the actual plotted values.

Rory Stark

dba.overlap

data(tamoxifen_peaks)
# peak overlap correlation heatmap
dba.plotHeatmap(tamoxifen)

data(tamoxifen_counts)
# counts correlation heatmap
dba.plotHeatmap(tamoxifen)

data(tamoxifen_analysis)
#correlation heatmap based on all normalized data
dba.plotHeatmap(tamoxifen,contrast=1,th=1)

#correlation heatmap based on DB sites only
dba.plotHeatmap(tamoxifen,contrast=1)

#binding heatmap based on DB sites
dba.plotHeatmap(tamoxifen,contrast=1,correlations=FALSE)

#binding heatmap based on 1,000 sites with highest variance
sites <- dba.plotHeatmap(tamoxifen,contrast=1,th=1,
                         correlations=FALSE,sortFun=var)
sites

data(tamoxifen_counts)
#Examples of  heatmaps using DB sites with different subsets of samples
#exclude T47D
tamoxifen <- dba.contrast(tamoxifen,design=FALSE,
                          group1=tamoxifen$masks$Resistant,
                          group2=c(3:5,10:11)) 
tamoxifen <- dba.analyze(tamoxifen)

# regular heatmaps with samples from two contrast groups only
dba.plotHeatmap(tamoxifen, contrast=1) 
#also include the T47D samples
dba.plotHeatmap(tamoxifen,contrast=1,mask=tamoxifen$masks$All) 

#correlation heatmap without MCF7 
plot(tamoxifen,contrast=1,mask=!tamoxifen$masks$MCF7) 

# binding heatmap using only the MCF7 samples
dba.plotHeatmap(tamoxifen,contrast=1,mask=tamoxifen$masks$MCF7,correlations=FALSE)