| reportTGIF | R Documentation | 
calcTGIF function
calcTGIF function calculates what kind of cellular patterns
and functional patterns are contained in single-cell RNA-seq data and
reportTGIF function generates report of analytic result.
reportTGIF(sce, out.dir=tempdir(), html.open=FALSE,
    title="The result of scTGIF",
    author="The person who runs this script",
    assayNames="counts")
sce | 
 A object generated by instantization of SingleCellExperiment-class.  | 
out.dir | 
 Output directory user want to save the report (Default: tempdir()).  | 
html.open | 
 Whether html is opened when   | 
title | 
 Title of report (Default: "The result of scTGIF")  | 
author | 
 The name of user name (Default: "The person who runs this script")  | 
assayNames | 
 The unit of gene expression for using scTGIF (e.g. normcounts, cpm...etc) (Default: "counts").  | 
Some file is generated to output directory user specified.
NA
    if(interactive()){
        # Package loading
        library("SingleCellExperiment")
        library("GSEABase")
        library("msigdbr")
        # Test data
        data("DistalLungEpithelium")
        data("pca.DistalLungEpithelium")
        data("label.DistalLungEpithelium")
        # Test data
        par(ask=FALSE)
        plot(pca.DistalLungEpithelium, col=label.DistalLungEpithelium, pch=16,
            main="Distal lung epithelium dataset", xlab="PCA1",
            ylab="PCA2", bty="n")
        text(0.1, 0.05, "AT1", col="#FF7F00", cex=2)
        text(0.07, -0.15, "AT2", col="#E41A1C", cex=2)
        text(0.13, -0.04, "BP", col="#A65628", cex=2)
        text(0.125, -0.15, "Clara", col="#377EB8", cex=2)
        text(0.09, -0.2, "Cilliated", col="#4DAF4A", cex=2)
        # Load the gmt file from MSigDB
        # Only "Entrez Gene ID" can be used in scTGIF
        # e.g. gmt <- GSEABase::getGmt(
        #     "/PATH/YOU/SAVED/THE/GMTFILES/h.all.v6.0.entrez.gmt")
        # Here we use msigdbr to retrieve mouse gene sets
        # Mouse gene set (NCBI Gene ID)
        m_df <- msigdbr(species = "Mus musculus", category = "H")[,
            c("gs_name", "entrez_gene")]
        # Convert to GeneSetCollection
        hallmark = unique(m_df$gs_name)
        gsc <- lapply(hallmark, function(h){
            target = which(m_df$gs_name == h)
            geneIds = unique(as.character(m_df$entrez_gene[target]))
            GeneSet(setName=h, geneIds)
        })
        gmt <- GeneSetCollection(gsc)
        # SingleCellExperiment-class
        sce <- SingleCellExperiment(
            assays = list(counts = DistalLungEpithelium))
        reducedDims(sce) <- SimpleList(PCA=pca.DistalLungEpithelium)
        # User's Original Normalization Function
        CPMED <- function(input){
            libsize <- colSums(input)
            median(libsize) * t(t(input) / libsize)
        }
        # Normalization
        normcounts(sce) <- log10(CPMED(counts(sce)) + 1)
        # Registration of required information into metadata(sce)
        settingTGIF(sce, gmt, reducedDimNames="PCA",
            assayNames="normcounts")
        # Functional Annotation based on jNMF
        calcTGIF(sce, ndim=7)
        # HTML Reprt
        reportTGIF(sce,
            html.open=TRUE,
            title="scTGIF Report for DistalLungEpithelium dataset",
            author="Koki Tsuyuzaki")
    }
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