hpaVisPatho {HPAanalyze} | R Documentation

## Visualize pathology data

### Description

Visualize the expression of genes of interest in each cancer.

### Usage

    hpaVisPatho(
      data = NULL,
      targetGene = NULL,
      targetCancer = NULL,
      color = c("#ffffb2", "#fecc5c", "#fd8d3c", "#e31a1c"),
      customTheme = FALSE
    )

### Arguments

`data` | Input the list object generated by `hpa_download()` or `hpa_subset()`. Require the `pathology` dataset. Use HPA histology data (built-in) by default.
`targetGene` | Vector of strings of HGNC gene symbols. By default it is set to `c('TP53', 'EGFR', 'CD44', 'PTEN', 'IDH1')`. You can also mix HGNC gene symbols and ensemnl ids (start with ENSG) and they will be converted to HGNC gene symbols.
`targetCancer` | Vector of strings of normal tissues. The function will plot all available cancer by default.
`color` | Vector of 4 colors used to depict different expression levels.
`customTheme` | Logical argument. If `TRUE`, the function will return a barebone ggplot2 plot to be customized further.

### Value

This function will return a ggplot2 plot object, which can be further modified if desirable. The pathology data is visualized as multiple bar graphs, one for each type of cancer. For each bar graph, x axis contains the inquired protein and y axis contains the proportion of patients.

### See Also

Other visualization functions: `hpaVisSubcell()`, `hpaVisTissue()`, `hpaVis()`

### Examples

      data("hpa_histology_data")
      geneList <- c('TP53', 'EGFR', 'CD44', 'PTEN', 'IDH1', 'IDH2', 'CYCS')
      cancerList <- c('breast cancer', 'glioma', 'melanoma')

      ## A typical function call
      hpaVisPatho(data=hpa_histology_data,
                     targetGene=geneList)

[Package HPAanalyze version 1.4.3 Index]