# run epiView/global.R
load_all("../epiView/epiDev/")
single_labels = rownames(dat[[1]]$res)
# group_labels = c(rep("GSK",19), rep("ENCODE",2))
# slice matrices if necessary
sample_ix = c(179:182,193:195,222,251)
for(i in 1:length(dat)) {
dat[[i]]$res = dat[[i]]$res[sample_ix,]
dat[[i]]$annot = dat[[i]]$annot[sample_ix,]
}
dat = dat[1:3] # remove atac (no data yet)
# a = melt(ldply(dat, function(z) {apply(z$res, 1, function(w) {ifelse(all(is.na(w)), 0, 1)})}))
# ggplot(a, aes(.id,variable, colour=as.factor(value))) + theme_thesis() +theme(axis.text.x=element_text(angle=45, hjust=1)) + geom_point(size=5) + labs(x="", y="", colour="present")
data_shape(dat)
# sub na for 0
for(i in 1:length(dat)) {
dat[[i]]$res[is.na(dat[[i]]$res)] = 0
}
d = newProject(
prepareData(
dat,
gene_list_all,
chr=NULL,
markerNames=names(dat),
trace=F
)
)
# set.seed(1)
# d_1 = subsetData(d) # withtout options, no data thinning is performed
# dim(d_1)
m = as.tensor(foldSubsetData(d$data))
cp_1 = cp(m, 5) # slider in app?
u_1 = cp_1$U[[1]]
rownames(u_1)=dimnames(m@data)[[1]]
u_3=cp_1$U[[3]]
marker_names = dimnames(m@data)[[3]]
col_table = list(
"A549"="A549",
"BEAS2B"="BEAS2B",
"NHBE"="NHBE"
)
pcs=c(1,2)
plot_grid(
simpleScoresPlot(u_1, pcs=pcs, colours=col_table, axes=F),
cpMarkerProfile(u_3, pcs, marker_names),
nrow=2, ncol=1,
rel_heights=c(3,1)
)
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