xEnrichForest | R Documentation

## Function to visualise enrichment results using a forest plot

### Description

`xEnrichForest` is supposed to visualise enrichment results using a forest plot. A point is colored by the significance level, and a horizontal line for the 95 the wider the CI, the less reliable). It returns an object of class "ggplot".

### Usage

    xEnrichForest(
    eTerm,
    top_num = 10,
    FDR.cutoff = 0.05,
    CI.one = T,
    colormap = "ggplot2.top",
    ncolors = 64,
    zlim = NULL,
    barwidth = 0.5,
    barheight = NULL,
    wrap.width = NULL,
    font.family = "sans",
    signature = FALSE,
    drop = F,
    sortBy = c("or", "adjp", "fdr", "pvalue", "zscore", "fc", "nAnno",
    "nOverlap", "none")
    )

### Arguments

`eTerm` | an object of class "eTerm" or "ls_eTerm". Alterntively, it can be a data frame having all these columns (named as 'group','ontology','name','adjp','or','CIl','CIu')
`top_num` | the number of the top terms (sorted according to OR). For the eTerm object, if it is 'auto' (for eTerm), only the significant terms (see below FDR.cutoff) will be displayed
`FDR.cutoff` | FDR cutoff used to declare the significant terms. By default, it is set to 0.05. Only works when top_num is 'auto' above
`CI.one` | logical to indicate whether to allow the inclusion of one in CI. By default, it is TURE (allowed)

`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

`ncolors` | the number of colors specified over the colormap
`zlim` | the minimum and maximum z values for which colors should be plotted, defaulting to the range of the -log10(FDR)
`barwidth` | the width of the colorbar. Default value is 'legend.key.width' or 'legend.key.size' in 'theme' or theme
`barheight` | the height of the colorbar. Default value is 'legend.key.height' or 'legend.key.size' in 'theme' or theme
`wrap.width` | a positive integer specifying wrap width of name
`font.family` | the font family for texts
`signature` | logical to indicate whether the signature is assigned to the plot caption. By default, it sets TRUE showing which function is used to draw this graph
`drop` | logical to indicate whether all factor levels not used in the data will automatically be dropped. If FALSE (by default), all factor levels will be shown, regardless of whether or not they appear in the data

`sortBy`

which statistics will be used for sorting and viewing gene sets (terms). It can be "adjp" or "fdr" for adjusted p value (FDR), "pvalue" for p value, "zscore" for enrichment z-score, "fc" for enrichment fold change, "nAnno" for the number of sets (terms), "nOverlap" for the number in overlaps, "or" for the odds ratio, and "none" for ordering according to ID of terms. It only works when the input is an eTerm object

### Value

an object of class "ggplot"

### Note

none

### See Also

`xEnricherGenes`, `xEnricherSNPs`, `xEnrichViewer`

### 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)

    # 1) Gene-based enrichment analysis using REACTOME pathways
    # perform enrichment analysis
    eTerm <- xEnricherGenes(data, ontology="REACTOME",
    RData.location=RData.location)
    ## forest plot of enrichment results
    gp <- xEnrichForest(eTerm, top_num="auto", FDR.cutoff=0.05)

    # 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)
    ## forest plot of enrichment results
    gp <- xEnrichForest(ls_eTerm, FDR.cutoff=0.1)

    ## End(Not run)