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added ks test scripts

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Tanushree Tunstall 2020-10-23 12:45:06 +01:00
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ks_test_all_timepoints.R Normal file
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#!/usr/bin/Rscript
getwd()
setwd('~/git/covid_analysis/')
getwd()
############################################################
# TASK: basic plots
# useful links:
# http://www.sthda.com/english/wiki/ggplot2-dot-plot-quick-start-guide-r-software-and-data-visualization
############################################################
# source data
source("read_data.R")
############################################################
#===================================
# output: KS test for cumulated time
#===================================
ks_all_timepoints = paste0(outdir_stats, "KS_test_all_timepoints_v3.csv")
############################################################
# data assignment for stats
wf = wf_data
lf = lf_data
#========================================================
# data assignment for stats
lf
sum(is.na(lf$value))
#lf = lf[!is.na(lf$value),]
#sum(is.na(lf$value))
#str(lf$value)
#========================================================
# ks test to analyse dist (all timepoints)
table(lf$outcomes, lf$mediator)
str(lf$outcomes)
table(lf$outcomes); str(lf$outcomes)
lf_death = lf[lf$outcomes==0,]
lf_recovered = lf[lf$outcomes==1,]
#=======================================================================
# for one
ks_pf = ks.test(lf_death$value[lf_death$mediator == "PF"]
, lf_recovered$value[lf_recovered$mediator == "PF"]); ks_pf
ks_srage = ks.test(lf_death$value[lf_death$mediator == "sRAGE"]
, lf_recovered$value[lf_recovered$mediator == "sRAGE"]); ks_srage
#=======================================================================
# loop
ks_df = data.frame()
mediator_names = levels(factor(lf$mediator))
for (i in mediator_names) {
df = data.frame(mediator = NA, test_name = NA, ks_statistic = NA, ks_pvalue = NA)
#df = data.frame()
#print(i)
ks.test(lf_death$value[lf_death$mediator == i]
, lf_recovered$value[lf_recovered$mediator == i])
med = i
ks_method = ks.test(lf_death$value[lf_death$mediator == i]
, lf_recovered$value[lf_recovered$mediator == i])$method
ks_statistic = ks.test(lf_death$value[lf_death$mediator == i]
, lf_recovered$value[lf_recovered$mediator == i])$statistic
ks_pval = ks.test(lf_death$value[lf_death$mediator == i]
, lf_recovered$value[lf_recovered$mediator == i])$p.value
#print(c(med, ks_method, ks_statistic[[1]], ks_pval))
df$mediator = med
df$test_name = ks_method
df$ks_statistic = ks_statistic[[1]]
df$ks_pvalue = ks_pval
print(df)
ks_df = rbind(ks_df, df)
}
#=======================================================================
# formatting
#=======================================================================
ks_df$group = "0 vs 1"
ks_df$timepoint = "t1,t2,t3"
str(ks_df)
ks_df$pvalue_signif = ks_df$ks_pvalue
str(ks_df$pvalue_signif)
# adding pvalue_signif
ks_df = dplyr::mutate(ks_df,pvalue_signif = case_when(pvalue_signif == 0.05 ~ "."
, pvalue_signif <=0.0001 ~ '****'
, pvalue_signif <=0.001 ~ '***'
, pvalue_signif <=0.01 ~ '**'
, pvalue_signif <0.05 ~ '*'
, TRUE ~ 'ns'))
#******************
# write output file: KS test
#******************
cat("Output of KS test all timeoints by group will be in:", ks_all_timepoints)
write.csv(ks_df, ks_all_timepoints, row.names = FALSE)