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added quick summary to see sig meds just before writing file

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Tanushree Tunstall 2020-11-20 12:36:55 +00:00
parent 17aebc26e8
commit 1562a09631
8 changed files with 63 additions and 29 deletions
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0
colnames_clinical_meds.R Normal file → Executable file
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0
data_extraction_formatting_clinical.R Normal file → Executable file
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0
data_extraction_formatting_non_asthmatics.R Normal file → Executable file
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data_extraction_formatting_regression.R Normal file → Executable file
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24
flu_stats_unpaired_na_npa.R
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@ -43,12 +43,6 @@ rm(pivot_cols)
# sanity checks
table(lf$timepoint)
#if (table(lf$flustat) == table(npa_lf$flustat)[[2]]){
# cat("Analysing Flu positive patients for:", my_sample_type)
#}else{
# cat("FAIL: problem with subsetting data for:", my_sample_type)
# quit()
#}
########################################################################
# Unpaired stats at each timepoint b/w groups: wilcoxon UNpaired analysis
# with correction
@ -366,16 +360,22 @@ colnames(combined_unpaired_stats_f) = c("mediator"
colnames(combined_unpaired_stats_f)
#---------------
# quick summary
#---------------
# count how many meds are significant
n_sig = length(combined_unpaired_stats_f$mediator[combined_unpaired_stats_f$p_signif<0.05])
cat("\nTotal no. of statistically significant mediators in", toupper(my_sample_type)
, "are:", n_sig)
n_sig = length(combined_unpaired_stats_f$mediator[combined_unpaired_stats_f$p_signif<0.05 & !is.na(combined_unpaired_stats_f$p_signif<0.05)])
sig_meds = combined_unpaired_stats_f[(combined_unpaired_stats_f$p_signif<0.05 & !is.na(combined_unpaired_stats_f$p_signif<0.05)),]
sig_meds = combined_unpaired_stats_f[combined_unpaired_stats_f$p_signif<0.05,]
sig_meds$med_time = paste0(sig_meds$mediator, "@", sig_meds$timepoint)
cat("\nTotal no. of statistically significant mediators in", toupper(my_sample_type)
, "are:", n_sig
, "\nThese are:", sig_meds$med_time)
########################################################################
#******************
# write output file
#******************
cat("UNpaired stats for groups will be:", flu_stats_time_unpaired_na)
write.csv(combined_unpaired_stats_f, flu_stats_time_unpaired_na, row.names = FALSE)
cat("\nUNpaired stats for groups will be:", flu_stats_time_unpaired_na)
#write.csv(combined_unpaired_stats_f, flu_stats_time_unpaired_na, row.names = FALSE)

18
flu_stats_unpaired_npa.R
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@ -366,16 +366,22 @@ colnames(combined_unpaired_stats_f) = c("mediator"
colnames(combined_unpaired_stats_f)
#---------------
# quick summary
#---------------
# count how many meds are significant
n_sig = length(combined_unpaired_stats_f$mediator[combined_unpaired_stats_f$p_signif<0.05])
cat("\nTotal no. of statistically significant mediators in", toupper(my_sample_type)
, "are:", n_sig)
n_sig = length(combined_unpaired_stats_f$mediator[combined_unpaired_stats_f$p_signif<0.05 & !is.na(combined_unpaired_stats_f$p_signif<0.05)])
sig_meds = combined_unpaired_stats_f[(combined_unpaired_stats_f$p_signif<0.05 & !is.na(combined_unpaired_stats_f$p_signif<0.05)),]
sig_meds = combined_unpaired_stats_f[combined_unpaired_stats_f$p_signif<0.05,]
sig_meds$med_time = paste0(sig_meds$mediator, "@", sig_meds$timepoint)
cat("\nTotal no. of statistically significant mediators in", toupper(my_sample_type)
, "are:", n_sig
, "\nThese are:", sig_meds$med_time)
########################################################################
#******************
# write output file
#******************
cat("UNpaired stats for groups will be:", flu_stats_time_unpaired)
write.csv(combined_unpaired_stats_f, flu_stats_time_unpaired, row.names = FALSE)
cat("\nUNpaired stats for groups will be:", flu_stats_time_unpaired)
#write.csv(combined_unpaired_stats_f, flu_stats_time_unpaired, row.names = FALSE)

22
flu_stats_unpaired_sam.R
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@ -71,8 +71,8 @@ foo = lf_t1[which(is.na(lf_t1$value)),]
lf_t1_comp = lf_t1[-which(is.na(lf_t1$value)),]
stats_un_t1 = compare_means(value~obesity
, group.by = "mediator"
, data = lf_t1
#, data = lf_t1_comp
#, data = lf_t1
, data = lf_t1_comp
, paired = FALSE
, p.adjust.method = my_adjust_method)
@ -368,9 +368,23 @@ colnames(combined_unpaired_stats_f) = c("mediator"
, "p_bon_signif")
colnames(combined_unpaired_stats_f)
#---------------
# quick summary
#---------------
# count how many meds are significant
n_sig = length(combined_unpaired_stats_f$mediator[combined_unpaired_stats_f$p_signif<0.05 & !is.na(combined_unpaired_stats_f$p_signif<0.05)])
sig_meds = combined_unpaired_stats_f[(combined_unpaired_stats_f$p_signif<0.05 & !is.na(combined_unpaired_stats_f$p_signif<0.05)),]
sig_meds$med_time = paste0(sig_meds$mediator, "@", sig_meds$timepoint)
cat("\nTotal no. of statistically significant mediators in", toupper(my_sample_type)
, "are:", n_sig
, "\nThese are:", sig_meds$med_time)
#######################################################################
#******************
# write output file
#******************
cat("UNpaired stats for groups will be:", flu_stats_time_unpaired)
write.csv(combined_unpaired_stats_f, flu_stats_time_unpaired, row.names = FALSE)
cat("\nUNpaired stats for groups will be:", flu_stats_time_unpaired)
#write.csv(combined_unpaired_stats_f, flu_stats_time_unpaired, row.names = FALSE)

28
flu_stats_unpaired_serum.R
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@ -67,8 +67,8 @@ ci = which(is.na(lf_t1$value))
lf_t1_comp = lf_t1[-which(is.na(lf_t1$value)),]
stats_un_t1 = compare_means(value~obesity
, group.by = "mediator"
, data = lf_t1
#, data = lf_t1_comp
#, data = lf_t1
, data = lf_t1_comp
, paired = FALSE
, p.adjust.method = my_adjust_method)
@ -129,8 +129,8 @@ lf_t2_comp = lf_t2[-which(is.na(lf_t2$value)),]
stats_un_t2 = compare_means(value~obesity
, group.by = "mediator"
, data = lf_t2
#, data = lf_t2_comp
#, data = lf_t2
, data = lf_t2_comp
, paired = FALSE
, p.adjust.method = my_adjust_method)
# add timepoint and convert to df
@ -188,8 +188,8 @@ lf_t3_comp = lf_t3[-which(is.na(lf_t3$value)),]
stats_un_t3 = compare_means(value~obesity
, group.by = "mediator"
, data = lf_t3
#, data = lf_t3_comp
#, data = lf_t3
, data = lf_t3_comp
, paired = FALSE
, p.adjust.method = my_adjust_method)
@ -361,9 +361,23 @@ colnames(combined_unpaired_stats_f) = c("mediator"
, "p_bon_signif")
colnames(combined_unpaired_stats_f)
#---------------
# quick summary
#---------------
# count how many meds are significant
n_sig = length(combined_unpaired_stats_f$mediator[combined_unpaired_stats_f$p_signif<0.05 & !is.na(combined_unpaired_stats_f$p_signif<0.05)])
sig_meds = combined_unpaired_stats_f[(combined_unpaired_stats_f$p_signif<0.05 & !is.na(combined_unpaired_stats_f$p_signif<0.05)),]
sig_meds$med_time = paste0(sig_meds$mediator, "@", sig_meds$timepoint)
cat("\nTotal no. of statistically significant mediators in", toupper(my_sample_type)
, "are:", n_sig
, "\nThese are:", sig_meds$med_time)
########################################################################
#******************
# write output file
#******************
cat("UNpaired stats for groups will be:", flu_stats_time_unpaired)
write.csv(combined_unpaired_stats_f, flu_stats_time_unpaired, row.names = FALSE)
#write.csv(combined_unpaired_stats_f, flu_stats_time_unpaired, row.names = FALSE)