ssvSignalHeatmap {seqsetvis} | R Documentation

## heatmap style representation of membership table. instead of clustering, each column is sorted starting from the left.

### Description

heatmap style representation of membership table. instead of clustering, each column is sorted starting from the left.

### Usage

    ssvSignalHeatmap(bw_data, nclust = 6, perform_clustering = c("auto", "yes",
      "no")[1], row_ = "id", column_ = "x", fill_ = "y", facet_ = "sample",
      cluster_ = "cluster_id", max_rows = 500, max_cols = 100,
      clustering_col_min = -Inf, clustering_col_max = Inf)

### Arguments

`bw_data` | a GRanges or data.table of bigwig signal. As returned from `ssvFetchBam` and `ssvFetchBigwig`
`nclust` | number of clusters
`perform_clustering` | should clustering be done? default is auto. auto considers if row_ has been ordered by being a factor and if cluster_ is a numeric.
`row_` | variable name mapped to row, likely peak id or gene name for ngs data
`column_` | varaible mapped to column, likely bp position for ngs data
`fill_` | numeric variable to map to fill
`facet_` | variable name to facet horizontally by
`cluster_` | variable name to use for cluster info
`max_rows` | for speed rows are sampled to 500 by default, use Inf to plot full data
`max_cols` | for speed columns are sampled to 100 by default, use Inf to plot full data
`clustering_col_min` | numeric minimum for col range considered when clustering, default in -Inf
`clustering_col_max` | numeric maximum for col range considered when clustering, default in Inf

### Value

ggplot heatmap of signal profiles, facetted by sample

### Examples

    #the simplest use
    ssvSignalHeatmap(CTCF_in_10a_profiles_gr)

    #clustering can be done manually beforehand
    clust_dt = ssvSignalClustering(CTCF_in_10a_profiles_gr, nclust = 3)
    ssvSignalHeatmap(clust_dt)

[Package seqsetvis version 1.0.2 Index]