plot_sample_corr_heatmap {proBatch} | R Documentation

## Sample correlation matrix (heatmap)

### Description

Plot correlation of selected samples

### Usage

    plot_sample_corr_heatmap(data_matrix, samples_to_plot = NULL,
      flavor = c("pheatmap", "corrplot"), filename = NULL, width = NA,
      height = NA, unit = c("cm", "in", "mm"),
      plot_title = sprintf("Correlation matrix of sample %s",
      samples_to_plot), ...)

### Arguments

`data_matrix` | features (in rows) vs samples (in columns) matrix, with feature IDs in rownames and file/sample names as colnames. Usually the log transformed version of the original data
`samples_to_plot` | string vector of samples in `data_matrix` to be used in the plot
`flavor` | either corrplot from 'corrplot' package or heatmap, as in 'pheatmap'
`filename` | path where the results are saved. If null the object is returned to the active window; otherwise, the object is save into the file. Currently only pdf and png format is supported
`width` | option determining the output image width
`height` | option determining the output image width
`unit` | units: 'cm', 'in' or 'mm'
`plot_title` | Title of the plot (usually, processing step + representation level (fragments, transitions, proteins))
`...` | parameters for the `corrplot.mixed` or `pheatmap` visualisation, for details see examples and help to corresponding functions

### Value

`corrplot` or `pheatmap` object depending on `flavor`

### See Also

`pheatmap`, `corrplot.mixed`

### Examples

    specified_samples = example_sample_annotation$FullRunName[
    which(example_sample_annotation$order %in% 110:115)]

    sample_corr_heatmap <- plot_sample_corr_heatmap(example_proteome_matrix,
    samples_to_plot = specified_samples,
     flavor = 'pheatmap',
     cluster_rows= FALSE, cluster_cols=FALSE,
     annotation_names_col = TRUE, annotation_legend = FALSE,
     show_colnames = FALSE)

[Package proBatch version 1.0.0 Index]