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1 changed files with 76 additions and 11 deletions
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@ -14,6 +14,7 @@ getwd()
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source("Header_TT.R")
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source("Header_TT.R")
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require(cowplot)
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require(cowplot)
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source("combining_dfs_plotting.R")
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source("combining_dfs_plotting.R")
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source("my_pairs_panel.R")
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# should return the following dfs, directories and variables
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# should return the following dfs, directories and variables
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# PS combined:
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# PS combined:
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@ -82,7 +83,58 @@ rm( merged_df2, merged_df2_comp, merged_df2_lig, merged_df2_comp_lig, my_df_u, m
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#===========================
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#===========================
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table(df_ps$duet_outcome)
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table(df_ps$duet_outcome)
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#===========================
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# Data for Correlation plots:foldx
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#===========================
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#============================
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# adding foldx scaled values
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# scale data b/w -1 and 1
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#============================
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n = which(colnames(df_ps) == "ddg"); n
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my_min = min(df_ps[,n]); my_min
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my_max = max(df_ps[,n]); my_max
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df_ps$foldx_scaled = ifelse(df_ps[,n] < 0
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, df_ps[,n]/abs(my_min)
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, df_ps[,n]/my_max)
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# sanity check
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my_min = min(df_ps$foldx_scaled); my_min
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my_max = max(df_ps$foldx_scaled); my_max
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if (my_min == -1 && my_max == 1){
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cat("PASS: foldx ddg successfully scaled b/w -1 and 1"
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, "\nProceeding with assigning foldx outcome category")
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}else{
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cat("FAIL: could not scale foldx ddg values"
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, "Aborting!")
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}
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#================================
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# adding foldx outcome category
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# ddg<0 = "Stabilising" (-ve)
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#=================================
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c1 = table(df_ps$ddg < 0)
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df_ps$foldx_outcome = ifelse(df_ps$ddg < 0, "Stabilising", "Destabilising")
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c2 = table(df_ps$ddg < 0)
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if ( all(c1 == c2) ){
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cat("PASS: foldx outcome successfully created")
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}else{
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cat("FAIL: foldx outcome could not be created. Aborting!")
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exit()
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}
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table(df_ps$foldx_outcome)
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#======================
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# adding log cols
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# adding log cols
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#======================
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df_ps$log10_or_mychisq = log10(df_ps$or_mychisq)
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df_ps$log10_or_mychisq = log10(df_ps$or_mychisq)
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df_ps$neglog_pval_fisher = -log10(df_ps$pval_fisher)
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df_ps$neglog_pval_fisher = -log10(df_ps$pval_fisher)
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@ -92,14 +144,21 @@ df_ps$neglog_pwald_kin = -log10(df_ps$pwald_kin)
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# subset data to generate pairwise correlations
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# subset data to generate pairwise correlations
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cols_to_select = c("duet_scaled"
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cols_to_select = c("duet_scaled"
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, "log10_or_mychisq"
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, "foldx_scaled"
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, "neglog_pval_fisher"
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#, "or_kin"
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#, "log10_or_mychisq"
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#, "neglog_pwald_kin"
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#, "neglog_pval_fisher"
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, "or_kin"
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, "neglog_pwald_kin"
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, "af"
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, "af"
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, "asa"
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, "rsa"
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, "kd_values"
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, "rd_values"
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, "duet_outcome"
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, "duet_outcome"
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, drug)
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, drug)
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@ -113,14 +172,20 @@ dim(corr_data_ps)
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# assign nice colnames (for display)
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# assign nice colnames (for display)
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my_corr_colnames = c("DUET"
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my_corr_colnames = c("DUET"
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, "Log(OR)"
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, "Foldx"
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, "-Log(P)"
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#, "Log(OR)"
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#, "-Log(P)"
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#, "OR adjusted"
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, "OR adjusted"
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#, "-Log(P wald)"
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, "-Log(P wald)"
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, "AF"
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, "AF"
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, "ASA"
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, "RSA"
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, "KD"
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, "RD"
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, "duet_outcome"
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, "duet_outcome"
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, drug)
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, drug)
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@ -161,9 +226,9 @@ OutPlot1 = pairs.panels(my_corr_ps[1:(length(my_corr_ps)-1)]
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, jitter = T
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, jitter = T
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#, alpha = .05
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#, alpha = .05
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#, points(pch = 19, col = c("#f8766d", "#00bfc4"))
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#, points(pch = 19, col = c("#f8766d", "#00bfc4"))
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, cex = 3
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, cex = 2
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, cex.axis = 2.5
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, cex.axis = 1.5
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, cex.labels = 2.1
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, cex.labels = 1.5
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, cex.cor = 1
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, cex.cor = 1
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, smooth = F
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, smooth = F
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)
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)
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