Visualize the expression of genes of interest in each cancer.
hpaVisPatho(
data = NULL,
targetGene = NULL,
targetCancer = NULL,
facetBy = "cancer",
color = c("#FCFDBF", "#FE9F6D", "#DE4968", "#8C2981"),
customTheme = FALSE
)Input the list object generated by hpa_download() or
hpa_subset(). Require the pathology dataset. Use HPA
histology data (built-in) by default.
Vector of strings of HGNC gene symbols. By default it is
set to c('TP53', 'EGFR', 'CD44', 'PTEN'). You can also mix HGNC gene
symbols and ensemnl ids (start with ENSG) and they will be converted to
HGNC gene symbols.
Vector of strings of normal tissues. The function will plot all available cancer by default.
Determine how multiple graphs would be faceted. Either
cancer (default) or gene.
Vector of 4 colors used to depict different expression levels.
Logical argument. If TRUE, the function will return
a barebone ggplot2 plot to be customized further.
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.
Other visualization functions:
hpaVisSubcell(),
hpaVisTissue(),
hpaVis()
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)
#> * WARNING: targetCancer variable not specified, visualize all.
#> >> Use hpaListParam() to list possible values for target variables.