plot_heatmap-methods: plot_heatmap method

In welch16/Segvis: Segvis: A package for visualization of high throughput sequencing data along genomic segments

Description

plot_heatmap plots a heatmap that summarizes the signal profiles of all files in the SegvisData object as a function of the distance to the center of the regions.

Usage

plot_heatmap(object, ...)

## S4 method for signature 'SegvisData'
plot_heatmap(object, which.cluster = 1,
  dist_method = "euclidean", clust_method = "complete",
  nameFiles = basename(files(object)), type = "aggr", base = 1e+06,
  mc.cores = getOption("mc.cores", 2L), ...)

Arguments

object	a SegvisData object.
...	Any other additional parameters that plot_heatmap may need.
which.cluster	an integer indicating which signal is going to be used to cluster the profiles. By default uses the first file loaded.
dist_method	the distance measure to be used. This must be one of "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski".
clust_method	the agglomeration method to be used. This should be one of "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC).
nameFiles	a character vector with the shortened names that are going to be used in the plot.
type	a character value indicating which strand to use. By default uses the aggregate coverage between both strands.
base	a numeric value indicating the number of aligned reads to which the signal is going to be normalized. The default value is 1e6. DT_profile always normalizes the signal.
mc.cores	a numeric value indicating the number of multi-cores to be used.

Value

The plot_heatmap plots a heatmap that summarizes the signal profiles of all files in the SegvisData object.

See Also

SegvisData-class

welch16/Segvis documentation built on May 4, 2019, 4:18 a.m.