## ----loadData-------------------------------------------------------------- library(compartmap) library(GenomicRanges) library(Homo.sapiens) #Load in some example methylation array data #This data is derived from https://f1000research.com/articles/5-1281/v3 #data(meth_array_450k_chr14, package = "compartmap") #Load in some example ATAC-seq data data(bulkATAC_raw_filtered_chr14, package = "compartmap") ## ----processData----------------------------------------------------------- #Process chr14 of the example array data #Note: running this in parallel is memory hungry! #array_compartments <- getCompartments(array.data.chr14, type = "array", parallel = FALSE, chrs = "chr14") #Process chr14 of the example ATAC-seq data atac_compartments <- getCompartments(filtered.data.chr14, type = "atac", parallel = FALSE, chrs = "chr14") ## ----clustering, eval = FALSE---------------------------------------------- # # #Plotting individual samples # #For 7 samples # #Adjust ylim as necessary # par(mar=c(1,1,1,1)) # par(mfrow=c(7,1)) # plotAB(array_compartments[,1], ylim = c(-0.2, 0.2), unitarize = TRUE) # plotAB(array_compartments[,2], ylim = c(-0.2, 0.2), unitarize = TRUE, top.col = "goldenrod") # plotAB(array_compartments[,3], ylim = c(-0.2, 0.2), unitarize = TRUE, top.col = "darkblue") # plotAB(array_compartments[,4], ylim = c(-0.2, 0.2), unitarize = TRUE, top.col = "red") # plotAB(array_compartments[,5], ylim = c(-0.2, 0.2), unitarize = TRUE, top.col = "black") # plotAB(array_compartments[,6], ylim = c(-0.2, 0.2), unitarize = TRUE, top.col = "cyan") # plotAB(array_compartments[,7], ylim = c(-0.2, 0.2), unitarize = TRUE, top.col = "seagreen") # # #Embed with UMAP for unsupervised clustering # library(uwot) # embed_compartments <- umap(t(array_compartments), n_neighbors = 3, metric = "manhattan", n_components = 5, n_trees = 100) # # #Visualize embedding # library(vizier) # library(plotly) # embed_plotly(embed_compartments, tooltip = colnames(embed_compartments), show_legend = FALSE) #