112 lines
4.2 KiB
R
Executable file
112 lines
4.2 KiB
R
Executable file
#!/usr/bin/Rscript
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getwd()
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setwd('~/git/covid_analysis/')
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getwd()
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############################################################
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# TASK: paired analysis on time for mediators
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############################################################
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# source data
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source("read_data.R")
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# clear unwanted variables
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rm(my_data)
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############################################################
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#=========================
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# output: paired_analysis
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#=========================
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stats_time_paired = paste0(outdir_stats, "stats_paired_v3.csv")
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############################################################
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# data assignment for stats
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wf = wf_data
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lf = lf_data
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########################################################################
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# Pairwise stats by timepoint: wilcoxon paired analysis with correction
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########################################################################
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# with adjustment: fdr and BH are identical
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my_adjust_method = "BH"
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stats_by_timepoint = compare_means(value~timepoint, group.by = "mediator"
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, data = lf
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, paired = TRUE
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, p.adjust.method = my_adjust_method)
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# check: satisfied!!!!
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wilcox.test(wf$sESelectin_ngmL_t1, wf$sESelectin_ngmL_t2, paired = T)
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wilcox.test(wf$sRAGE_pgmL_t1, wf$sRAGE_pgmL_t2, paired = T)
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# delete unnecessary column
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stats_by_timepoint = subset(stats_by_timepoint, select = -c(.y.))
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# reflect stats method correctly
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stats_by_timepoint$method
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stats_by_timepoint$method = gsub("Wilcoxon", "Wilcoxon_paired", stats_by_timepoint$method)
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stats_by_timepoint$method
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# replace "." in colnames with "_"
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colnames(stats_by_timepoint)
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#names(stats_by_timepoint) = gsub("\.", "_", names(stats_by_timepoint)) # weird!!!!
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colnames(stats_by_timepoint) = c("mediator"
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,"group1"
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,"group2"
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,"p"
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,"p_adj"
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,"p_format"
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,"p_signif"
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,"method" )
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colnames(stats_by_timepoint)
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# add an extra column for padjust_signif
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stats_by_timepoint$padjust_signif = round(stats_by_timepoint$p_adj, digits = 2)
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# add appropriate symbols for padjust_signif
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#stats_by_timepoint = stats_by_timepoint %>%
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# mutate(padjust_signif = case_when(padjust_signif == 0.05 ~ "."
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# , padjust_signif <0.05 ~ '*'
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# , padjust_signif <=0.01 ~ '**'
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# , padjust_signif <=0.001 ~ '***'
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# , padjust_signif <=0.0001 ~ '****'
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# , TRUE ~ 'ns'))
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stats_by_timepoint = dplyr::mutate(stats_by_timepoint, padjust_signif = case_when(padjust_signif == 0.05 ~ "."
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, padjust_signif <=0.0001 ~ '****'
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, padjust_signif <=0.001 ~ '***'
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, padjust_signif <=0.01 ~ '**'
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, padjust_signif <0.05 ~ '*'
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, TRUE ~ 'ns'))
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# reorder columns
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print("preparing to reorder columns...")
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colnames(stats_by_timepoint)
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my_col_order2 = c("mediator"
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, "group1"
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, "group2"
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, "method"
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, "p"
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, "p_format"
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, "p_signif"
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, "p_adj"
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, "padjust_signif")
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if( length(my_col_order2) == ncol(stats_by_timepoint) && isin(my_col_order2, colnames(stats_by_timepoint)) ){
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print("PASS: Reordering columns...")
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stats_by_timepoint_f = stats_by_timepoint[, my_col_order2]
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print("Successful: column reordering")
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print("formatted df called:'stats_by_timepoint_f'")
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cat('\nformatted df has the following dimensions\n')
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print(dim(stats_by_timepoint_f ))
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} else{
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cat(paste0("FAIL:Cannot reorder columns, length mismatch"
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, "\nExpected column order for: ", ncol(stats_by_timepoint)
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, "\nGot:", length(my_col_order2)))
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quit()
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}
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#******************
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# write output file
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#******************
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cat("Paired stats by timepoint will be:", stats_time_paired)
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write.csv(stats_by_timepoint_f, stats_time_paired, row.names = FALSE)
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