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358_stats_on_flow_cyt.R
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suppressMessages(library("plyr", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("data.table", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("crayon", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("withr", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("ggplot2", lib.loc = "/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("farver", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("labeling", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("optparse", lib.loc = "/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("dplyr", lib.loc = "/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("withr", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("backports", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("broom", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("rstudioapi", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("cli", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("tzdb", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("tidyverse", lib.loc="/nfs/team151/software/manuel_R_libs_4_1//"))
suppressMessages(library("svglite", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("ggeasy", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("sandwich", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("digest", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
suppressMessages(library("ggforce", lib.loc="/nfs/team151/software/manuel_R_libs_4_1/"))
library("lme4", lib.loc = "/nfs/team151/software/manuel_R_libs_4_1/")
library("afex", lib.loc = "/nfs/team151/software/manuel_R_libs_4_1/")
opt = NULL
#options(warn = 1)
Stats_function = function(option_list)
{
opt_in = option_list
opt <<- option_list
cat("All options:\n")
printList(opt)
#### READ and transform type ----
type = opt$type
cat("TYPE_\n")
cat(sprintf(as.character(type)))
cat("\n")
#### READ and transform out ----
out = opt$out
cat("OUT_\n")
cat(sprintf(as.character(out)))
cat("\n")
#### Read Flow_cyt_data ----
Flow_cyt_data<-as.data.frame(fread(file=opt$Flow_cyt_data, sep=",") , stringsAsFactors=F)
cat("Flow_cyt_data_0\n")
cat(str(Flow_cyt_data))
cat("\n")
cat(sprintf(as.character(names(summary(as.factor(Flow_cyt_data$Genotype))))))
cat("\n")
cat(sprintf(as.character(summary(as.factor(Flow_cyt_data$Genotype)))))
cat("\n")
cat(sprintf(as.character(names(summary(as.factor(Flow_cyt_data$Time))))))
cat("\n")
cat(sprintf(as.character(summary(as.factor(Flow_cyt_data$Time)))))
cat("\n")
cat(sprintf(as.character(names(summary(as.factor(Flow_cyt_data$Condition))))))
cat("\n")
cat(sprintf(as.character(summary(as.factor(Flow_cyt_data$Condition)))))
cat("\n")
Basal.df<-Flow_cyt_data[which(Flow_cyt_data$Condition == 'unst'),]
cat("Basal.df_0\n")
cat(str(Basal.df))
cat("\n")
cols<-colnames(Basal.df)[5:dim(Basal.df)[2]]
cat("cols_0\n")
cat(str(cols))
cat("\n")
Basal.df.dt<-data.table(Basal.df, key=c("Sample","Genotype"))
Basal.df.addition <- as.data.frame(Basal.df.dt[, sapply(.SD, function(x) list(mean = mean(x))), .SDcols = cols, by = key(Basal.df.dt)], stringsAsFactors=F)
colnames(Basal.df.addition)<-gsub("\\.mean","",colnames(Basal.df.addition))
cat("Basal.df.addition_0\n")
cat(str(Basal.df.addition))
cat("\n")
Basal.df.addition_new_1 <- Basal.df.addition[rep(seq_len(nrow(Basal.df.addition)), each = 3), ]
Basal.df.addition_new_1<-Basal.df.addition_new_1[order(Basal.df.addition_new_1$Sample,Basal.df.addition_new_1$Genotype),]
cat("Basal.df.addition_new_1_0\n")
cat(str(Basal.df.addition_new_1))
cat("\n")
Basal.df.addition_new_1$Time<-'Basal'
Basal.df.addition_new_1$Condition<-rep(c("unst","PMA","Hemin"),(dim(Basal.df.addition_new_1)[1]/3))
cat("Basal.df.addition_new_1_1\n")
cat(str(Basal.df.addition_new_1))
cat("\n")
# ############################
# quit(status = 1)
Flow_cyt_data<-rbind(Flow_cyt_data,Basal.df.addition_new_1)
##### Transform into ordered factors ----
Flow_cyt_data$Genotype<-factor(Flow_cyt_data$Genotype,
levels=c("WT","KI","Del"),
ordered=T)
Flow_cyt_data$Time<-factor(Flow_cyt_data$Time,
levels=c("Basal","24","96"),
ordered=T)
Flow_cyt_data$Condition<-factor(Flow_cyt_data$Condition,
levels=c("unst","PMA","Hemin"),
ordered=T)
cat("Flow_cyt_data_1\n")
cat(str(Flow_cyt_data))
cat("\n")
cat(sprintf(as.character(names(summary(Flow_cyt_data$Genotype)))))
cat("\n")
cat(sprintf(as.character(summary(Flow_cyt_data$Genotype))))
cat("\n")
cat(sprintf(as.character(names(summary(Flow_cyt_data$Time)))))
cat("\n")
cat(sprintf(as.character(summary(Flow_cyt_data$Time))))
cat("\n")
cat(sprintf(as.character(names(summary(Flow_cyt_data$Condition)))))
cat("\n")
cat(sprintf(as.character(summary(Flow_cyt_data$Condition))))
cat("\n")
#### Summary table parameters----
cols<-colnames(Flow_cyt_data)[5:dim(Flow_cyt_data)[2]]
cat("cols_0\n")
cat(str(cols))
cat("\n")
Flow_cyt_data.dt<-data.table(Flow_cyt_data, key=c("Genotype","Condition","Time"))
Summary_table_parameters_mean <- as.data.frame(Flow_cyt_data.dt[, sapply(.SD, function(x) list(mean = mean(x))), .SDcols = cols, by = key(Flow_cyt_data.dt)], stringsAsFactors=F)
cat("Summary_table_parameters_mean_0\n")
cat(str(Summary_table_parameters_mean))
cat("\n")
Summary_table_parameters_mean.m<-melt(Summary_table_parameters_mean, id.vars=c("Genotype","Condition","Time"),value.name = "Mean",variable.name = "Parameter")
Summary_table_parameters_mean.m$Parameter<-gsub("\\.mean","",Summary_table_parameters_mean.m$Parameter)
cat("Summary_table_parameters_mean.m_0\n")
cat(str(Summary_table_parameters_mean.m))
cat("\n")
cat(sprintf(as.character(names(summary(as.factor(Summary_table_parameters_mean.m$Parameter))))))
cat("\n")
cat(sprintf(as.character(summary(as.factor(Summary_table_parameters_mean.m$Parameter)))))
cat("\n")
Summary_table_parameters_sd <- as.data.frame(Flow_cyt_data.dt[, sapply(.SD, function(x) list(sd = sd(x))), .SDcols = cols, by = key(Flow_cyt_data.dt)], stringsAsFactors=F)
cat("Summary_table_parameters_sd_0\n")
cat(str(Summary_table_parameters_sd))
cat("\n")
Summary_table_parameters_sd.m<-melt(Summary_table_parameters_sd, id.vars=c("Genotype","Condition","Time"),value.name = "sd",variable.name = "Parameter")
Summary_table_parameters_sd.m$Parameter<-gsub("\\.sd","",Summary_table_parameters_sd.m$Parameter)
cat("Summary_table_parameters_sd.m_0\n")
cat(str(Summary_table_parameters_sd.m))
cat("\n")
cat(sprintf(as.character(names(summary(as.factor(Summary_table_parameters_sd.m$Parameter))))))
cat("\n")
cat(sprintf(as.character(summary(as.factor(Summary_table_parameters_sd.m$Parameter)))))
cat("\n")
Summary_table_DEF<-merge(Summary_table_parameters_mean.m,
Summary_table_parameters_sd.m,
by=c("Genotype","Condition","Time","Parameter"))
Summary_table_DEF$Parameter<-factor(Summary_table_DEF$Parameter,
levels=c('CD41+','CD41-CD235+','CD41+CD235-','CD41+CD235+','CD41 GeoMFI','CD235 GeoMFI'),
ordered=T)
cat("Summary_table_DEF_0\n")
cat(str(Summary_table_DEF))
cat("\n")
cat(sprintf(as.character(names(summary(Summary_table_DEF$Parameter)))))
cat("\n")
cat(sprintf(as.character(summary(Summary_table_DEF$Parameter))))
cat("\n")
Summary_table_DEF<-Summary_table_DEF[order(Summary_table_DEF$Parameter,Summary_table_DEF$Genotype,Summary_table_DEF$Condition,Summary_table_DEF$Time),]
cat("Summary_table_DEF_1\n")
cat(str(Summary_table_DEF))
cat("\n")
cat(sprintf(as.character(names(summary(Summary_table_DEF$Parameter)))))
cat("\n")
cat(sprintf(as.character(summary(Summary_table_DEF$Parameter))))
cat("\n")
#### LOOP to ITERATE the GENOTYPES ----
Genotypes_array<-levels(Flow_cyt_data$Genotype)
Condition_DEBUG <- 1
for(i in 1:length(Genotypes_array))
{
Genotype_sel<-Genotypes_array[i]
cat("------------------>\t")
cat(sprintf(as.character(Genotype_sel)))
cat("\n")
if(i > 1)
{
comparison<-c(Genotypes_array[1],Genotypes_array[i])
cat("----------comparison-------->\t")
cat(sprintf(as.character(comparison)))
cat("\n")
comparison_string<-paste(comparison, collapse="_")
Flow_cyt_data_sel<-droplevels(Flow_cyt_data[which(Flow_cyt_data$Genotype%in%comparison),])
cat("Flow_cyt_data_sel_0\n")
cat(str(Flow_cyt_data_sel))
cat("\n")
# cat(sprintf(as.character(names(summary(Flow_cyt_data_sel$Genotype)))))
# cat("\n")
# cat(sprintf(as.character(summary(Flow_cyt_data_sel$Genotype))))
# cat("\n")
# cat(sprintf(as.character(names(summary(Flow_cyt_data_sel$Time)))))
# cat("\n")
# cat(sprintf(as.character(summary(Flow_cyt_data_sel$Time))))
# cat("\n")
# cat(sprintf(as.character(names(summary(Flow_cyt_data_sel$Condition)))))
# cat("\n")
# cat(sprintf(as.character(summary(Flow_cyt_data_sel$Condition))))
# cat("\n")
for(k in 5:dim(Flow_cyt_data_sel)[2])
{
continuous_variable_sel<-colnames(Flow_cyt_data_sel)[k]
cat("--->\t")
cat(sprintf(as.character(continuous_variable_sel)))
cat("\n")
path5<-paste(out,continuous_variable_sel,'/', sep='')
if (file.exists(path5)){
} else {
dir.create(file.path(path5))
}
# indx.parameter_sel<-which(colnames(Flow_cyt_data_sel) == continuous_variable_sel)
#
#
# cat("indx.parameter_sel\n")
# cat(str(indx.parameter_sel))
# cat("\n")
Summary_table_DEF_sel<-droplevels(Summary_table_DEF[which(Summary_table_DEF$Parameter == continuous_variable_sel &
Summary_table_DEF$Genotype%in%comparison),])
cat("Summary_table_DEF_sel_0\n")
cat(str(Summary_table_DEF_sel))
cat("\n")
#### model CD41+CD235- ----
full_model<-lmer(Flow_cyt_data_sel[,k] ~ 1 + Genotype:Time +
Genotype + Time + Condition +
(1 + Genotype|Sample) + (1 + Genotype|Condition), data= Flow_cyt_data_sel)
check_full_model<-isSingular(full_model, tol = 1e-4)
# cat("check_full_model\n")
# cat(str(check_full_model))
# cat("\n")
Summary_model<-summary(full_model)
intermediate_model<-lmer(Flow_cyt_data_sel[,k] ~ 1 +
Genotype + Time + Condition +
(1 + Genotype|Sample) + (1 + Genotype|Condition), data= Flow_cyt_data_sel)
check_intermediate_model<-isSingular(intermediate_model, tol = 1e-4)
# cat("check_intermediate_model\n")
# cat(str(check_intermediate_model))
# cat("\n")
Summary_model<-summary(intermediate_model)
# cat("Summary_model\n")
# cat(str(Summary_model))
# cat("\n")
reduced_model<-lmer(Flow_cyt_data_sel[,k] ~ 1 +
Time + Condition +
(1 + Genotype|Sample) + (1 + Genotype|Condition), data= Flow_cyt_data_sel)
check_reduced_model<-isSingular(reduced_model, tol = 1e-4)
# cat("check_reduced_model\n")
# cat(str(check_reduced_model))
# cat("\n")
LRT_model_intermediate<-anova(reduced_model,intermediate_model)
cat("LRT_model_intermediate\n")
cat(str(LRT_model_intermediate))
cat("\n")
LRT_model_full<-anova(intermediate_model,full_model)
cat("LRT_model_full\n")
cat(str(LRT_model_full))
cat("\n")
setwd(path5)
write.table(LRT_model_full, file=paste("LRT_model_full_",comparison_string,".tsv",sep=''), sep="\t", quote=F)
write.table(LRT_model_intermediate, file=paste("LRT_model_intermediate_",comparison_string,".tsv",sep=''), sep="\t", quote=F)
coefficients<-Summary_model$coefficients
# cat("coefficients\n")
# cat(str(coefficients))
# cat("\n")
write.table(coefficients, file=paste("coefficients_",comparison_string,".tsv",sep=''), sep="\t", quote=F)
# if(continuous_variable_sel == 'CD41+' &
# comparison_string == 'WT_Del')
# {
# cat("Summary_model\n")
# cat(str(Summary_model))
# cat("\n")
#
# quit(status = 1)
#
# }
#### GRAPH ----
A<-summary(Summary_table_DEF_sel$Mean)
if(Condition_DEBUG == 1)
{
cat("A\n")
cat(sprintf(as.character(names(A))))
cat("\n")
cat(sprintf(as.character(A)))
cat("\n")
}
max_value<-A[6]
min_value<-A[1]
step<-round((max_value-min_value)/4,2)
if(Condition_DEBUG == 1)
{
cat("max_value:min_value:step\n")
cat(sprintf(as.character(max_value)))
cat("\t")
cat(sprintf(as.character(min_value)))
cat("\t")
cat(sprintf(as.character(step)))
cat("\n")
}
if(step == 0)
{
step<-2
breaks.Parameter<-sort(unique(c(0,seq(min_value,max_value, by=step),max_value)))
labels.Parameter<-as.character(round(breaks.Parameter,2))
}else{
breaks.Parameter<-sort(unique(c(0,seq(min_value,max_value, by=step),max_value)))
labels.Parameter<-as.character(round(breaks.Parameter,2))
}
g_line<-ggplot(Summary_table_DEF_sel,
aes(x=Time,
y=Mean)) +
geom_point(aes(shape=Genotype,
color=Condition,
fill=Condition),size=3,stroke=2)+
geom_errorbar(aes(ymin=Mean-sd, ymax=Mean+sd,
color=Condition), width=.2,
position=position_dodge(0.05))+
theme_classic()+
scale_shape_manual(name = paste("Genotype","of","Clone",sep="\n"), values = c("WT"=15,"KI"=16,"Del"=17), breaks=c("WT","KI","Del"), drop=T) +
scale_color_manual(values=c('unst'="grey70", 'PMA'="brown", 'Hemin'="firebrick1"), drop=T)+
scale_fill_manual(values=c('unst'="grey70", 'PMA'="brown", 'Hemin'="firebrick1"), drop=T)+
scale_y_continuous(name=paste(continuous_variable_sel),
breaks=breaks.Parameter,labels=labels.Parameter,
limits=c(breaks.Parameter[1]-5,breaks.Parameter[length(breaks.Parameter)]+15))+
scale_x_discrete(name="Time")+
theme(axis.title.y=element_text(size=18, color="black", family="sans"),
axis.title.x=element_blank(),
axis.text.y=element_text(angle=0,size=14, color="black", family="sans"),
axis.text.x=element_text(angle=0,size=14, color="black", family="sans"))+
theme(legend.position="right")+
ggeasy::easy_center_title()
setwd(path5)
svglite(paste("Graph",'_',comparison_string,'.svg', sep =''))
print(g_line)
dev.off()
# quit(status = 1)
}# k in 5:dim(Flow_cyt_data_sel)[2]
}# don't select 'WT' genotype is the reference
}#i in 1:length(Genotypes_array)
}
printList = function(l, prefix = " ") {
list.df = data.frame(val_name = names(l), value = as.character(l))
list_strs = apply(list.df, MARGIN = 1, FUN = function(x) { paste(x, collapse = " = ")})
cat(paste(paste(paste0(prefix, list_strs), collapse = "\n"), "\n"))
}
#### main script ----
main = function() {
cmd_line = commandArgs()
cat("Command line:\n")
cat(paste(gsub("--file=", "", cmd_line[4], fixed=T),
paste(cmd_line[6:length(cmd_line)], collapse = " "),
"\n\n"))
option_list <- list(
make_option(c("--Table_of_labels"), type="character", default=NULL,
metavar="type",
help="Path to tab-separated input file listing regions to analyze. Required."),
make_option(c("--Flow_cyt_data"), type="character", default=NULL,
metavar="type",
help="Path to tab-separated input file listing regions to analyze. Required."),
make_option(c("--tracking_variants"), type="character", default=NULL,
metavar="type",
help="Path to tab-separated input file listing regions to analyze. Required."),
make_option(c("--type"), type="character", default=NULL,
metavar="type",
help="Path to tab-separated input file listing regions to analyze. Required."),
make_option(c("--out"), type="character", default=NULL,
metavar="filename",
help="Path to tab-separated input file listing regions to analyze. Required.")
)
parser = OptionParser(usage = "140__Rscript_v106.R
--subset type
--TranscriptEXP FILE.txt
--cadd FILE.txt
--ncboost FILE.txt
--type type
--out filename",
option_list = option_list)
opt <<- parse_args(parser)
Stats_function(opt)
}
###########################################################################
system.time( main() )