Broad BM examples

library(pagoda2)
library(dplyr)
library(conos)
library(parallel)
library(cowplot)
library(ggrepel)
library(Matrix)
library(data.table)
# some extra code for the comparative analysis here
source("/home/pkharchenko/m/pavan/DLI/conp2.r")

cdl <- readRDS("~/m/p2/examples/broadBM/full/full.cdl.rds")

Take complete patient 1 matrices, filter

cdl <- cdl[grep("MantonBM1",names(cdl))]
common.genes <- Reduce(intersect,lapply(cdl,rownames))
cdl <- lapply(cdl,function(x) x[common.genes,colSums(x)>500])
old.ann <- readRDS("~/m/p2/examples/figures/fig1/base.ann.rds")
cell.sizes <- lapply(cdl,colSums)
cell.sizes <- setNames(unlist(cell.sizes),unlist(lapply(cell.sizes,names)))

Conos integration to transfer labels: pre-processing

cdl.p2 <- lapply(cdl, basicP2proc, n.cores=30, min.cells.per.gene=0, n.odgenes=2e3, get.largevis=FALSE, make.geneknn=FALSE,get.tsne=T)

Integrate

con <- Conos$new(cdl.p2,n.cores=30)
con$buildGraph(k=15, k.self=5, space='PCA', ncomps=30, n.odgenes=2000, matching.method='mNN', metric='angular', verbose=TRUE)

Cluster and generate a 2D ebmedding

con$findCommunities(r=2)
con$embedGraph(method='UMAP'); 
emb <- con$embedding;

con$misc$embeddings <- list(UMAP=emb)

con$embedGraph(method='largeVis'); 
con$misc$embeddings <- list(largeVis=emb)

propagate labels

new.ann <- con$propagateLabels(labels = old.ann, verbose=T,fixed.initial.labels=TRUE)
new.ann <- new.ann$labels

Take a look:

alpha <- 0.1; size <- 0.1;
p1 <- con$plotGraph(title='clusters',alpha=alpha,size=size);
p2 <- con$plotGraph(color.by='sample',title='samples',mark.groups=F,alpha=alpha,size=size);
p3 <- con$plotGraph(groups=new.ann,alpha=alpha,size=size,title='annotation',plot.na=F)
p4 <- con$plotGraph(colors=cell.sizes,alpha=alpha,size=size,title='depth')
cowplot::plot_grid(plotlist=list(p1,p2,p3,p4),nrow=2)

con$plotPanel(groups=new.ann)