View source: R/xEnrichTreemap.r
xEnrichTreemap | R Documentation |
xEnrichTreemap
is supposed to visualise enrichment results using
a treemap. The area is proportional to odds ratio, colored by the
significance level. It returns an object of class "ggplot".
xEnrichTreemap( eTerm, top_num = 10, FDR.cutoff = 0.05, CI.one = T, colormap = "spectral.top", ncolors = 64, zlim = NULL, barwidth = NULL, barheight = 0.5, wrap.width = NULL, font.family = "sans", drop = F, details = c("name", "name_FDR", "name_FDR_members"), caption = T, treemap.grow = F, treemap.reflow = F, treemap.place = "topleft", treemap.color = "black", treemap.fontface = "bold.italic", treemap.min.size = 4, area = c("adjp", "or"), area.fill = c("or", "adjp", "zscore") )
eTerm |
an object of class "eTerm" or "ls_eTerm". Alterntively, it can be a data frame having these columns (named as 'group','ontology','name','zscore','adjp','or','CIl','CIu','nOverlap','members_Overlap') in which 'name','zscore','adjp','or','CIl','CIu' are required |
top_num |
the number of the top terms (sorted according to OR). If it is 'auto', 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 |
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 |
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 |
details |
how to label. It can be one of 'name', 'name_FDR' (FDR/OR also appended to the name), and 'name_FDR_members' (FDR/OR plus members appended to the name; in this case, treemap.grow and treemap.reflow is forced to be true) |
caption |
logical to indicate whether the caption is shown on the bottom-right |
treemap.grow |
logical to indicate whether text will be grown as well as shrunk to fill the box |
treemap.reflow |
logical to indicate whether text will be reflowed (wrapped) to better fit the box |
treemap.place |
where inside the box to place the text. Default is "centre"; other options are "bottom", "top", "topleft", "topright", etc |
treemap.color |
the color of the text |
treemap.fontface |
the fontface of the text |
treemap.min.size |
the minimum font size, in points. If provided, text that would need to be shrunk below this size to fit the box will not be drawn. Defaults to 4 pt |
area |
which statistics will be used for the area. It can be "adjp" for adjusted p value (FDR) and "or" for odds ratio |
area.fill |
which statistics will be used for the area fill color. It can be "or" for the odds ratio, "adjp" for adjusted p value (FDR) and "zscore" for enrichment z-score |
an object of class "ggplot"
none
xEnricherGenes
, xEnricherSNPs
,
xEnrichViewer
## Not run: # Load the library library(XGR) RData.location <- "http://galahad.well.ox.ac.uk/bigdata/" library(treemapify) # 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 <- xEnrichTreemap(eTerm, top_num=20, FDR.cutoff=0.05, treemap.reflow=F, treemap.place="topleft") # 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 <- xEnrichTreemap(ls_eTerm, FDR.cutoff=0.1) ## End(Not run)
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