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stats_unpaired.R
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#!/usr/bin/Rscript
getwd()
setwd('~/git/covid_analysis/')
getwd()
############################################################
# TASK: unpaired analysis for mediators at each timepoint
############################################################
# source data
source("read_data.R")
# clear unwanted variables
rm(my_data)
############################################################
#============================
# Output: unpaired analysis
#============================
stats_time_unpaired = paste0(outdir_stats, "stats_unpaired_v3.csv")
############################################################
# data assignment for stats
wf = wf_data
lf = lf_data
########################################################################
# Unpaired stats at each timepoint b/w groups: wilcoxon UNpaired analysis with correction
#######################################################################
# with adjustment: fdr and BH are identical
my_adjust_method = "BH"
#==============
# unpaired: t1
#==============
lf_t1 = lf[lf$timepoint == "t1",]
stats_un_t1 = compare_means(value~outcomes, group.by = "mediator"
, data = lf_t1
, paired = FALSE
, p.adjust.method = my_adjust_method)
stats_un_t1$timepoint = "t1"
stats_un_t1 = as.data.frame(stats_un_t1)
class(stats_un_t1)
# check: satisfied!!!!
wilcox.test(wf$sESelectin_ngmL_t1[wf$outcomes == 0], wf$sESelectin_ngmL_t1[wf$outcomes == 1]
, paired = FALSE)
wilcox.test(wf$PF_units_t1[wf$outcomes==0], wf$PF_units_t1[wf$outcomes == 1]
, paired = FALSE)
#==============
# unpaired: t2
#==============
lf_t2 = lf[lf$timepoint == "t2",]
stats_un_t2 = compare_means(value~outcomes, group.by = "mediator"
, data = lf_t2
, paired = FALSE
, p.adjust.method = my_adjust_method)
stats_un_t2$timepoint = "t2"
stats_un_t2 = as.data.frame(stats_un_t2)
class(stats_un_t2)
# check: satisfied!!!!
wilcox.test(wf$sESelectin_ngmL_t2[wf$outcomes == 0], wf$sESelectin_ngmL_t2[wf$outcomes == 1]
, paired = FALSE)
wilcox.test(wf$PF_units_t2[wf$outcomes==0], wf$PF_units_t2[wf$outcomes == 1]
, paired = FALSE)
#==============
# unpaired: t3
#==============
lf_t3 = lf[lf$timepoint == "t3",]
stats_un_t3 = compare_means(value~outcomes, group.by = "mediator"
, data = lf_t3
, paired = FALSE
, p.adjust.method = my_adjust_method)
stats_un_t3$timepoint = "t3"
stats_un_t3 = as.data.frame(stats_un_t3)
class(stats_un_t3)
# check: satisfied!!!!
wilcox.test(wf$sESelectin_ngmL_t3[wf$outcomes == 0], wf$sESelectin_ngmL_t3[wf$outcomes == 1]
, paired = FALSE)
wilcox.test(wf$PF_units_t3[wf$outcomes==0], wf$PF_units_t3[wf$outcomes == 1]
, paired = FALSE)
#==============
# Rbind these dfs
#==============
str(stats_un_t1);str(stats_un_t2); str(stats_un_t3)
n_dfs = 3
if ( all.equal(nrow(stats_un_t1), nrow(stats_un_t2), nrow(stats_un_t3)) &&
all.equal(ncol(stats_un_t1), ncol(stats_un_t2), ncol(stats_un_t3)) ) {
expected_rows = nrow(stats_un_t1) * n_dfs
expected_cols = ncol(stats_un_t1)
print("PASS: expected_rows and cols variables generated for downstream sanity checks")
}else{
cat("FAIL: dfs have different no. of rows and cols"
, "\nCheck harcoded value of n_dfs"
, "\nexpected_rows and cols could not be generated")
quit()
}
if ( all.equal(colnames(stats_un_t1), colnames(stats_un_t2), colnames(stats_un_t3)) ){
print("PASS: colnames match. Rbind the 3 dfs...")
combined_unpaired_stats = rbind(stats_un_t1, stats_un_t2, stats_un_t3)
} else{
cat("FAIL: cannot combined dfs. Colnames don't match!")
quit()
}
if ( nrow(combined_unpaired_stats) == expected_rows && ncol(combined_unpaired_stats) == expected_cols ){
cat("PASS: combined_df has expected dimension"
, "\nNo. of rows in combined_df:", nrow(combined_unpaired_stats)
, "\nNo. of cols in combined_df:", ncol(combined_unpaired_stats) )
}else{
cat("FAIL: combined_df dimension mismatch")
quit()
}
#===============================================================
# formatting df
# delete unnecessary column
combined_unpaired_stats = subset(combined_unpaired_stats, select = -c(.y.))
# reflect stats method correctly
combined_unpaired_stats$method
combined_unpaired_stats$method = gsub("Wilcoxon", "Wilcoxon_unpaired", combined_unpaired_stats$method)
combined_unpaired_stats$method
# replace "." in colnames with "_"
colnames(combined_unpaired_stats)
#names(combined_unpaired_stats) = gsub("\.", "_", names(combined_unpaired_stats)) # weird!!!!
colnames(combined_unpaired_stats) = c("mediator"
,"group1"
,"group2"
,"p"
,"p_adj"
,"p_format"
,"p_signif"
,"method"
, "timepoint")
colnames(combined_unpaired_stats)
# add an extra column for padjust_signif
combined_unpaired_stats$padjust_signif = round(combined_unpaired_stats$p_adj, digits = 2)
# add appropriate symbols for padjust_signif
#combined_unpaired_stats = combined_unpaired_stats %>%
# mutate(padjust_signif = case_when(padjust_signif == 0.05 ~ "."
# , padjust_signif <0.05 ~ '*'
# , padjust_signif <=0.01 ~ '**'
# , padjust_signif <=0.001 ~ '***'
# , padjust_signif <=0.0001 ~ '****'
# , TRUE ~ 'ns'))
combined_unpaired_stats = dplyr::mutate(combined_unpaired_stats, padjust_signif = case_when(padjust_signif == 0.05 ~ "."
, padjust_signif <=0.0001 ~ '****'
, padjust_signif <=0.001 ~ '***'
, padjust_signif <=0.01 ~ '**'
, padjust_signif <0.05 ~ '*'
, TRUE ~ 'ns'))
# reorder columns
print("preparing to reorder columns...")
colnames(combined_unpaired_stats)
my_col_order2 = c("mediator"
, "timepoint"
, "group1"
, "group2"
, "method"
, "p"
, "p_format"
, "p_signif"
, "p_adj"
, "padjust_signif")
if( length(my_col_order2) == ncol(combined_unpaired_stats) && isin(my_col_order2, colnames(combined_unpaired_stats)) ){
print("PASS: Reordering columns...")
combined_unpaired_stats_f = combined_unpaired_stats[, my_col_order2]
print("Successful: column reordering")
print("formatted df called:'combined_unpaired_stats_f'")
cat('\nformatted df has the following dimensions\n')
print(dim(combined_unpaired_stats_f ))
} else{
cat(paste0("FAIL:Cannot reorder columns, length mismatch"
, "\nExpected column order for: ", ncol(combined_unpaired_stats)
, "\nGot:", length(my_col_order2)))
quit()
}
#******************
# write output file
#******************
cat("UNpaired stats for groups will be:", stats_time_unpaired)
write.csv(combined_unpaired_stats_f, stats_time_unpaired, row.names = FALSE)