xEnrichHeatmap | R Documentation

## Function to visualise enrichment results using heatmap

### Description

`xEnrichHeatmap` is supposed to visualise enrichment results using heatmap. It returns an object of class "ggplot".

### Usage

    xEnrichHeatmap(list_eTerm, fdr.cutoff = 0.05, displayBy = c("zscore",
    "fdr", "pvalue", "fc", "or"), colormap = NULL, zlim = NULL,
    reorder = c("none", "row", "col", "both"))

### Arguments

`list_eTerm` | an object of class "ls_eTerm". Alterntively, it can be a data frame having all these columns (named as 'group','ontology','name','adjp') and one of these columns ("zscore","fdr","pvalue","fc","or"). Note, the column 'fdr' can be inferred from the column 'adjp'
`fdr.cutoff` | FDR cutoff used to declare the significant terms. By default, it is set to 0.05
`displayBy` | which statistics will be used for comparison. It can be "fc" for enrichment fold change (by default), "adjp" for adjusted p value (or FDR), "pvalue" for p value, "zscore" for enrichment z-score, "or" for enrichment odd ratio
`colormap` | short name for the colormap. It can be one of "jet" (jet colormap), "bwr" (blue-white-red colormap), "gbr" (green-black-red colormap), "wyr" (white-yellow-red colormap), "br" (black-red colormap), "yr" (yellow-red colormap), "wb" (white-black colormap), and "rainbow" (rainbow colormap, that is, red-yellow-green-cyan-blue-magenta). Alternatively, any hyphen-separated HTML color names, e.g. "blue-black-yellow", "royalblue-white-sandybrown", "darkgreen-white-darkviolet". A list of standard color names can be found in http://html-color-codes.info/color-names
`zlim` | the minimum and maximum z values for which colors should be plotted, defaulting to the range of the -log10(FDR)
`reorder` | how to reorder rows and columns. It can be "none" for no reordering, "row" for reordering rows according to number of sharings (by default), "col" for reordering columns, and "both" for reordering rows and columns

### Value

an object of class "ggplot"

### Note

none

### See Also

`xHeatmap`

### Examples

    ## Not run:
    # Load the library
    library(XGR)
    RData.location <- "http://galahad.well.ox.ac.uk/bigdata/"

    # provide the input Genes of interest (eg 100 randomly chosen human genes)
    ## load human genes
    org.Hs.eg <- xRDataLoader(RData='org.Hs.eg',
    RData.location=RData.location)
    set.seed(825)
    data <- as.character(sample(org.Hs.eg$gene_info$Symbol, 100))
    data

    # optionally, provide the test background (if not provided, all human genes)
    #background <- as.character(org.Hs.eg$gene_info$Symbol)

    # 2) Gene-based enrichment analysis using ontologies (REACTOME and GOMF)
    # perform enrichment analysis
    ls_eTerm <- xEnricherGenesAdv(data, ontologies=c("REACTOME","GOMF"),
    RData.location=RData.location)
    ## heatmap plot of enrichment results
    gp <- xEnrichHeatmap(ls_eTerm, fdr.cutoff=0.1, displayBy="zscore")

    ## End(Not run)