plotHeatmaps: plot heatmaps of ChIP-seq experiments
In ChIPSeqSpike: ChIP-Seq data scaling according to spike-in control

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

Clusters and output binding values signal in the form of heatmaps

  plotHeatmaps(theObject, location = "start", 
                transformType = "spiked", legend = TRUE, plot_scale = "no",
                sort_rows = "decreasing", nb_of_groups = 1, 
                clustering_method = "none", include_exp_vec = NULL, 
                auto_scale = FALSE, raster_value = FALSE, col_value = "blue",
                ...)

## S4 method for signature 'ChIPSeqSpikeDataset'
plotHeatmaps(theObject, location = "start", 
transformType = "spiked", legend = TRUE, plot_scale = "no", sort_rows = 
"decreasing", nb_of_groups = 1, clustering_method = "none", include_exp_vec = 
NULL, auto_scale = FALSE, raster_value = FALSE, col_value = "blue", ...)

## S4 method for signature 'ChIPSeqSpikeDatasetBoost'
plotHeatmaps(theObject, location = 
"start", transformType = "spiked", legend = TRUE, plot_scale = "no", 
sort_rows = "decreasing", nb_of_groups = 1, clustering_method = "none", 
include_exp_vec = NULL, auto_scale = FALSE, raster_value = FALSE, 
col_value = "blue", ...)

## S4 method for signature 'ChIPSeqSpikeDatasetList'
plotHeatmaps(theObject, location = "start",
transformType = "spiked", legend = TRUE, plot_scale = "no", sort_rows = 
"decreasing", nb_of_groups = 1, clustering_method = "none", include_exp_vec = 
NULL, auto_scale = FALSE, raster_value = FALSE, col_value = "blue", ...)

## S4 method for signature 'ChIPSeqSpikeDatasetListBoost'
plotHeatmaps(theObject, location = 
"start", transformType = "spiked", legend = TRUE, plot_scale = "no", 
sort_rows = "decreasing", nb_of_groups = 1, clustering_method = "none", 
include_exp_vec = NULL, auto_scale = FALSE, raster_value = FALSE, 
col_value = "blue", ...)

`theObject`	`ChIPSeqSpike` dataset (see ?spikeDataset)
`location`	Define the location at which heatmaps should be plotted. Possible values are 'start', 'midpoint', 'end' and 'composite' (see details). Default is 'start'.
`transformType`	Indicate what step of chip-seq spike-in normalization is used. Possible values are 'spiked', 'reverse', 'BGSub' 'RPM' and 'raw' (see details). Default is 'spiked'. Not available in boost mode.
`legend`	Logical indicating if legend should be indicated. Default is FALSE.
`plot_scale`	Indicate the transformation that is applied to the data before plotting. Possible values are 'no' (default), 'linear', 'log2' or 'zscore'. See ?seqplots::plotHeatmap for more details.
`sort_rows`	Indicate how rows of the heatmap should be sorted. Possible values are 'increasing', 'decreasing' or FALSE. See ?seqplots::plotHeatmap for more details. Default is 'decreasing'.
`nb_of_groups`	If clustering_method is different than 'none', define the number of groups of the cluster. Default is 1.
`clustering_method`	Determine the heatmap clustering algorithm. Possible values are 'k-means', 'hclust', 'ssom', 'bed_scores' and 'none'. See ?seqplots::plotHeatmap for more details. Default is 'none'.
`include_exp_vec`	Logical vector indicating on which experiments clustering is performed. NULL meaning all experiments. See ?seqplots::plotHeatmap for more details. Default is NULL.
`auto_scale`	Logical indicating if color scaled should be specific to each experiment. Default is FALSE.
`raster_value`	Logical indicating if the bitmap raster is used. See ?seqplots::plotHeatmap for more details. Default is FALSE.
`col_value`	The vector or list of colour values used generate sub-heatmaps colorspaces. See ?seqplots::plotHeatmap for more details. Default is 'blue'.
`...`	Additional parameter to pass to seqplots::plotHeatmap.

This method relies on the 'plotHeatmap' method of the 'seqplots' package and enables to generate different heatmaps on the chIPSeqSpike objects (see ?spikeDataset).

The 'transformType' indicates if the untransformed (raw), RPM scaled (RPM), input subtracted (BGSub), RPM reversed (reverse) or spiked (spiked) data should be used to generate the heatmaps. This option is only available if not in boost mode (see ?spikePipe for details on what these steps are).

See ?seqplots::plotHeatmap for details.

ChIPSeqSpikeDataset: Method for signature theObject= 'ChIPSeqSpikeDataset'
ChIPSeqSpikeDatasetBoost: Method for signature theObject= 'ChIPSeqSpikeDatasetBoost'
ChIPSeqSpikeDatasetList: Method for signature theObject= 'ChIPSeqSpikeDatasetList'
ChIPSeqSpikeDatasetListBoost: Method for signature theObject= 'ChIPSeqSpikeDatasetListBoost'

Nicolas Descostes

spikeDataset spikePipe plotHeatmap plotProfile plotTransform boxplotSpike plotCor

data("result_extractBinding")

## Spiked data in decreasing order
plotHeatmaps(csds)

## Raw data in decreasing order
plotHeatmaps(csds, transformType = "raw")

## K-means clustering with 3 groups
plotHeatmaps(csds, nb_of_groups = 3, clustering_method = "kmeans")