hpaVisPatho: Visualize pathology data

In HPAanalyze: Retrieve and analyze data from the Human Protein Atlas

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)

HPAanalyze documentation built on Nov. 26, 2020, 2:01 a.m.