diff --git a/r.scripts/sc-TissueMapper.R b/r.scripts/sc-TissueMapper.R
index 37ad9f9655fe9d440bc8cb3ea3718be8e3c98f4b..38adbeced40df00083db4cf7401eeddc1aaec1dc 100644
--- a/r.scripts/sc-TissueMapper.R
+++ b/r.scripts/sc-TissueMapper.R
@@ -492,14 +492,6 @@ scQuSAGE <- function(sc10x,gs,res.use=0.1,ds=25000,nm="Lin",folder="lin"){
labels <- paste0("Cluster_",as.vector(factor(sc10x@ident)))
- #if ((ncol(sc10x@data)>ds & ds!=0)){
- # rnd <- sample(1:ncol(sc10x@data),ds)
- # data <- sc10x@data[,rnd]
- # labels <- labels[rnd]
- #} else {
- # data <- sc10x@data
- #}
-
cell.sample <- NULL
for (i in 1:number.clusters){
cell <- names(sc10x@ident[sc10x@ident==i])
@@ -651,16 +643,7 @@ scQuSAGEsm <- function(sc10x,gs,ds=25000,nm="Lin",folder="lin"){
clusters <- unique(sc10x@ident)
labels <- as.vector(factor(sc10x@ident))
-
- #if ((ncol(sc10x@data)>ds & ds!=0)){
- # rnd <- sample(1:ncol(sc10x@data),ds)
- # data <- sc10x@data[,rnd]
- # labels <- labels[rnd]
- #} else {
- # data <- sc10x@data
- #}
- #data <- as.data.frame(as.matrix(data))
-
+
cell.sample <- NULL
for (i in clusters){
cell <- names(sc10x@ident[sc10x@ident==i])
@@ -773,15 +756,6 @@ scQuSAGElg <- function(sc10x,gs,ds=25000,nm="Lin",folder="lin"){
labels <- as.vector(factor(sc10x@ident))
- #if ((ncol(sc10x@data)>ds & ds!=0)){
- # rnd <- sample(1:ncol(sc10x@data),ds)
- # data <- sc10x@data[,rnd]
- # labels <- labels[rnd]
- #} else {
- # data <- sc10x@data
- #}
- #data <- as.data.frame(as.matrix(data))
-
cell.sample <- NULL
for (i in clusters){
cell <- names(sc10x@ident[sc10x@ident==i])
diff --git a/r.scripts/sc-TissueMapper_RUN.Pd.R b/r.scripts/sc-TissueMapper_RUN.Pd.R
index 285435076c104a486dafec8c09290f7831bfef99..b954f3624a695f8ffe1cceedaff14311a9d79417 100644
--- a/r.scripts/sc-TissueMapper_RUN.Pd.R
+++ b/r.scripts/sc-TissueMapper_RUN.Pd.R
@@ -3,7 +3,6 @@ library(methods)
library(optparse)
library(Seurat)
library(readr)
-#library(readxl)
library(fBasics)
library(pastecs)
library(qusage)
@@ -104,18 +103,11 @@ option_list=list(
make_option("--cca",action="store",default=50,type='integer',help="Number of CCAs to cacluate"),
make_option("--acca",action="store",default=30,type='integer',help="Number of CCAs to align"),
make_option("--pc",action="store",default=50,type='integer',help="Number of PCs to cacluate"),
- #make_option("--hpc",action="store",default=0.9,type='numeric',help="Max variance cutoff for PCs to use, pre-stress"),
make_option("--res.prestress",action="store",default=1,type='numeric',help="Resolution to cluster, pre-stress"),
make_option("--st",action="store",default=TRUE,type='logical',help="Remove stressed cells?"),
make_option("--stg",action="store",default="go",type='character',help="Geneset to use for stress ID"),
make_option("--cut.stress",action="store",default=0.9,type='numeric',help="Cutoff for stress score"),
- #make_option("--hpc.poststress",action="store",default=0.85,type='numeric',help="Max variance cutoff for PCs to use, post-stress"),
make_option("--res.poststress",action="store",default=0.2,type='numeric',help="Resolution to cluster, post-stress"),
- #make_option("--ds",action="store",default=250,type='integer',help="Number of cells to downsample"),
- #make_option("--hpc.epi",action="store",default=0.85,type='numeric',help="Max variance cutoff for PCs to use, Epi"),
- #make_option("--res.epi",action="store",default=0.2,type='numeric',help="Resolution to cluster, Epi"),
- #make_option("--hpc.st",action="store",default=0.85,type='numeric',help="Max variance cutoff for PCs to use, St"),
- #make_option("--res.st",action="store",default=0.15,type='numeric',help="Resolution to cluster, St"),
make_option("--cut.ne",action="store",default=0.999,type='numeric',help="Cutoff for NE score")
)
opt=parse_args(OptionParser(option_list=option_list))
@@ -164,14 +156,7 @@ rm(sc10x.D17)
rm(sc10x.D27)
rm(sc10x.D35)
-#results <- scPC(sc10x,lx=opt$lx,hx=opt$hx,ly=opt$ly,cc=opt$cc,pc=opt$pc,hpc=opt$hpc,file="pre.stress",cca=TRUE)
-#sc10x <- results[[1]]
-#genes.hvg.prestress <- results[[2]]
-#pc.use.prestress <- results[[3]]
-#rm(results)
-
sc10x <- scCluster(sc10x,pc.use=opt$acca,res.use=opt$res.prestress,folder="pre.stress",red="cca.aligned")
-#sc10x <- scCluster(sc10x,pc.use=pc.use.prestress,res.use=opt$res.prestress,folder="pre.stress",red="pca")
if (opt$st==TRUE){
results <- scStress(sc10x,stg=opt$stg,res.use=opt$res.prestress,cut=opt$cut.stress)
@@ -180,17 +165,7 @@ if (opt$st==TRUE){
sc10x.Stress <- results[[3]]
rm(results)
- #results <- scPC(sc10x,lx=opt$lx,hx=opt$hx,ly=opt$ly,cc=opt$cc,pc=opt$pc,hpc=opt$hpc,file="post.stress",cca=FALSE)
- #sc10x <- results[[1]]
- #genes.hvg.poststress <- results[[2]]
- #pc.use.poststress <- results[[3]]
- #rm(results)
-
- #sc10x <- scCluster(sc10x,pc.use=pc.use.poststress,res.use=opt$res.poststress,folder="post.stress",red="pca")
sc10x <- scCluster(sc10x,pc.use=opt$acca,res.use=opt$res.poststress,folder="post.stress",red="cca.aligned")
- #sc10x <- scCluster(sc10x,pc.use=opt$acca,res.use=0.15,folder="post.stress",red="cca.aligned")
- #sc10x <- scCluster(sc10x,pc.use=opt$acca,res.use=0.25,folder="post.stress",red="cca.aligned")
- #sc10x <- scCluster(sc10x,pc.use=opt$acca,res.use=0.5,folder="post.stress",red="cca.aligned")
}
gene.set1 <- read_delim("./genesets/DEG_Epi_5FC.txt","\t",escape_double=FALSE,trim_ws=TRUE,col_names=FALSE)
@@ -303,12 +278,6 @@ gc()
results.cor.Epi.lgea <- scQuSAGEsm(sc10x.Epi,gs=gene.set,ds=min.epi,nm="Epi.dws.sub",folder="lgea")
rm(gene.set)
-#sc10x.St <- scCluster(sc10x.St,pc.use=opt$acca,res.use=opt$res.st,folder="st",red="cca.aligned")
-#sc10x.St <- scCluster(sc10x.St,pc.use=opt$acca,res.use=0.2,folder="st",red="cca.aligned")
-#sc10x.St <- scCluster(sc10x.St,pc.use=opt$acca,res.use=0.25,folder="st",red="cca.aligned")
-#sc10x.St <- scCluster(sc10x.St,pc.use=opt$acca,res.use=0.5,folder="st",red="cca.aligned")
-#sc10x.St <- scCluster(sc10x.St,pc.use=opt$acca,res.use=0.1,folder="st",red="cca.aligned")
-
sc10x.St <- RunTSNE(object=sc10x.St,reduction.use="cca.aligned",dims.use=1:opt$acca,do.fast=TRUE)
postscript(paste0("./analysis/tSNE/st/tSNE_Sample.eps"))
plot <- TSNEPlot(object=sc10x.St,group.by="samples",pt.size=2.5,do.return=TRUE,vector.friendly=FALSE)
@@ -363,7 +332,6 @@ sc10x <- scMerge(sc10x,sc10x,sc10x.Epi.NE,i.1="Merge_Epi.dws_St.go",i.2="NE",nm=
sc10x.Epi <- scMerge(sc10x.Epi,sc10x.Epi,sc10x.Epi.NE,i.1="Epi.dws.sub",i.2="NE",nm="Epi.dws.sub_NE")
gene.orthog <- read.delim("./genesets/Ensemble.mus-hum.txt")
-#gene.set1 <- read_excel("./genesets/SupTab3_Consensus_Sigs.xlsx",skip=5)
gene.set1 <- read_csv("./genesets/SupTab3_Consensus_Sigs.csv",skip=6)
gene.set2 <- as.data.frame(gene.set1$Basal[!is.na(gene.set1$Basal)])
colnames(gene.set2) <- "genes"
@@ -402,7 +370,6 @@ gene.set2 <- as.list(gene.set2)
names(gene.set2) <- "Ionocyte"
gene.set <- c(gene.set,gene.set2)
rm(gene.set2)
-#gene.set1 <- read_excel("./genesets/SupTab6_Krt13_Hillock.xlsx",skip=5)
gene.set1 <- read_csv("./genesets/SupTab6_Krt13_Hillock.csv",skip=6)
gene.set1 <- gene.set1[gene.set1$FDR<=0.05 & gene.set1$'log2 fold-change (MAST)'>=1.5,1]
colnames(gene.set1) <- "genes"