renamed count_vars_ML previous version as such
This commit is contained in:
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14e655eeeb
commit
a5d22540e1
9 changed files with 336 additions and 185 deletions
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@ -22,13 +22,12 @@ outfile_merged_df3 = paste0(outdir, '/', tolower(gene), '_merged_df3.csv')
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# Add acticve site indication
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###############################################
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merged_df2$active_site = as.integer(merged_df2$position %in% active_aa_pos)
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#merged_df2_comp$active_site = as.integer(merged_df2_comp$position %in% active_aa_pos)
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merged_df3$active_site = as.integer(merged_df3$position %in% active_aa_pos)
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#merged_df3_comp$active_site = as.integer(merged_df3_comp$position %in% active_aa_pos)
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# check
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cols_sel = c('mutationinformation', 'mutation_info_labels', 'dm_om_numeric', 'dst', 'dst_mode')
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cols_sel = c('mutationinformation', 'mutation_info_labels'
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#, 'dm_om_numeric'
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, 'dst', 'dst_mode')
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check_mdf2 = merged_df2[, cols_sel]
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check_mdf2T = table(check_mdf2$mutationinformation, check_mdf2$dst_mode)
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@ -42,8 +41,8 @@ dst_check = all((ft_mdf2[,1]==0)==(ft_mdf2[,2]!=0)); dst_check
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#=======================
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# CHECK: dst mode labels
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#=======================
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table(merged_df2$mutation_info_labels_orig)
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table(merged_df2$mutation_info_labels_v1)
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#table(merged_df2$mutation_info_labels_orig)
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#table(merged_df2$mutation_info_labels_v1)
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table(merged_df2$mutation_info_labels)
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dst_check1 = table(merged_df2$dst_mode)[1] == table(merged_df2$mutation_info_labels)[2]
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@ -75,184 +74,61 @@ gene
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gene_match
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nrow(merged_df3)
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###########################################
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#========================
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# CHECK: drtype: revised labels [Merged_df2]
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#=========================
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table(merged_df2$drtype) #orig
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table(merged_df2$drtype_mode)
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# mapping 2.1: numeric
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# drtype_map = {'XDR': 5
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# , 'Pre-XDR': 4
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# , 'MDR': 3
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# , 'Pre-MDR': 2
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# , 'Other': 1
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# , 'Sensitive': 0}
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# create a labels col that is mapped based on drtype_mode
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merged_df2$drtype_mode_labels = merged_df2$drtype_mode
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merged_df2$drtype_mode_labels = as.factor(merged_df2$drtype_mode)
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levels(merged_df2$drtype_mode_labels)
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levels(merged_df2$drtype_mode_labels) <- c('Sensitive', 'Other'
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, 'Pre-MDR', 'MDR'
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, 'Pre-XDR', 'XDR')
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levels(merged_df2$drtype_mode_labels)
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# check
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a1 = all(table(merged_df2$drtype_mode) == table(merged_df2$drtype_mode_labels))
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b1 = sum(table(merged_df2$drtype_mode_labels)) == nrow(merged_df2)
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if (all(a1 && b1)){
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cat("\nPASS: added drtype mode labels to merged_df2")
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}else{
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stop("FAIL: could not add drtype mode labels to merged_df2")
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##quit()
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}
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#################################################
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#=======================
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# CHECK: drtype: revised labels [merged_df3]
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#=======================
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table(merged_df3$drtype) #orig
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table(merged_df3$drtype_mode)
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# mapping 2.1: numeric
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# drtype_map = {'XDR': 5
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# , 'Pre-XDR': 4
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# , 'MDR': 3
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# , 'Pre-MDR': 2
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# , 'Other': 1
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# , 'Sensitive': 0}
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# create a labels col that is mapped based on drtype_mode
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merged_df3$drtype_mode_labels = merged_df3$drtype_mode
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merged_df3$drtype_mode_labels = as.factor(merged_df3$drtype_mode)
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levels(merged_df3$drtype_mode_labels)
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levels(merged_df3$drtype_mode_labels) <- c('Sensitive', 'Other'
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, 'Pre-MDR', 'MDR'
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, 'Pre-XDR', 'XDR')
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levels(merged_df3$drtype_mode_labels)
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a2 = all(table(merged_df3$drtype_mode) == table(merged_df3$drtype_mode_labels))
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b2 = sum(table(merged_df3$drtype_mode_labels)) == nrow(merged_df3)
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# check
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if (all(a2 && b2)){
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cat("\nPASS: added drtype mode labels to merged_df3")
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}else{
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stop("FAIL: could not add drtype mode labels to merged_df3")
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##quit()
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}
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#===============
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# CHECK: lineage
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#===============
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l1 = table(merged_df3$lineage) == table(merged_df3$lineage_labels)
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l2 = table(merged_df2$lineage) == table(merged_df2$lineage_labels)
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l3 = sum(table(merged_df2$lineage_labels)) == nrow(merged_df2)
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l4 = sum(table(merged_df3$lineage_labels)) == nrow(merged_df3)
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if (all(l1 && l2 && l3 && l4) ){
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cat("\nPASS: lineage and lineage labels are identical!")
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}else{
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stop("FAIL: could not verify lineage labels")
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##quit()
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}
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###############################################
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# #=============
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# # mutation_info: revised labels
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# #==============
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# table(merged_df3$mutation_info)
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# sum(table(merged_df3$mutation_info))
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# table(merged_df3$mutation_info_orig)
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##############################################
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# #=============
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# # <drug>, dst_mode: revised labels
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# #==============
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# table(merged_df3$dst) # orig
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# sum(table(merged_df3$dst))
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#
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# table(merged_df3$dst_mode)
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# #table(merged_df3[dr_muts_col])
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# sum(table(merged_df3$drtype_mode))
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##############################################
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if ( all( check12 && aa_check1 && aa_check2 && a1 && b1 && a2 && b2 && l1 && l2 && l3 && l4) ){
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cat("\nWriting merged_dfs for:"
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, "\nDrug:", drug
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, "\nGene:", gene)
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write.csv(merged_df3, outfile_merged_df3)
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#write.csv(merged_df2, outfile_merged_df2)
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cat(paste("\nmerged df3 filename:", outfile_merged_df3
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write.csv(merged_df3, outfile_merged_df3)
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#write.csv(merged_df2, outfile_merged_df2)
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cat(paste("\nmerged df3 filename:", outfile_merged_df3
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#, "\nmerged df2 filename:", outfile_merged_df2)
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))
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} else{
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stop("FAIL: Not able to write merged dfs. Please check numbers!")
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#quit()
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}
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#%%###################################################################
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# check merged_df3
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check_mdf3 = merged_df3[, cols_sel]
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check_mdf3T = table(check_mdf3$mutationinformation, check_mdf3$dst_mode)
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ft_mdf3 = as.data.frame.matrix(check_mdf3T)
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#==================
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# CHECK: dst mode
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#===================
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dst_check_mdf3 = all((ft_mdf3[,1]==0)==(ft_mdf3[,2]!=0)); dst_check_mdf3
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sel = c("mutationinformation", "dst", "dst_mode")
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a = merged_df3[, sel]
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str(a)
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###################################################
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###################################################
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###################################################
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source("~/git/LSHTM_analysis/config/alr.R")
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source("~/git/LSHTM_analysis/config/embb.R")
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source("~/git/LSHTM_analysis/config/gid.R")
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source("~/git/LSHTM_analysis/config/katg.R")
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source("~/git/LSHTM_analysis/config/pnca.R")
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source("~/git/LSHTM_analysis/config/rpob.R")
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#
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# source("~/git/LSHTM_analysis/config/alr.R")
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# source("~/git/LSHTM_analysis/config/embb.R")
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# source("~/git/LSHTM_analysis/config/gid.R")
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# source("~/git/LSHTM_analysis/config/katg.R")
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# source("~/git/LSHTM_analysis/config/pnca.R")
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# source("~/git/LSHTM_analysis/config/rpob.R")
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# #
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df3_filename = paste0("/home/tanu/git/Data/", drug, "/output/", tolower(gene), "_merged_df3.csv")
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df3 = read.csv(df3_filename)
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#
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# #
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# mutationinformation
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length(unique((df3$mutationinformation)))
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# #
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# # #dm _om
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# table(df3$mutation_info)
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# #table(df3$mutation_info_orig)
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# #table(df3$mutation_info_labels_orig)
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#
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# #dm _om
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table(df3$mutation_info)
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table(df3$mutation_info_orig)
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table(df3$mutation_info_labels_orig)
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# used in plots and analyses
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table(df3$mutation_info_labels) # different, and matches dst_mode
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table(df3$dst_mode)
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# test_set
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na_count <-sapply(df3, function(y) sum(length(which(is.na(y)))))
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na_count[drug]
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# # used in plots and analyses
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# table(df3$mutation_info_labels) # different, and matches dst_mode
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# table(df3$dst_mode)
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#
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# # test_set
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# na_count <-sapply(df3, function(y) sum(length(which(is.na(y)))))
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# na_count[drug]
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# #
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# # # training set
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# table(df3[drug])
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# #
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# # # drtype: MDR and XDR
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# # #table(df3$drtype) orig i.e. incorrect ones!
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# # table(df3$drtype_mode_labels)
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#
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# # training set
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table(df3[drug])
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#
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# # drtype: MDR and XDR
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# #table(df3$drtype) orig i.e. incorrect ones!
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# table(df3$drtype_mode_labels)
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df3_complete = df3
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table(df3_complete$dst_mode)
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comp_lin_all = df3_complete[df3_complete$lineage_labels%in%c("L1", "L2", "L3", "L4"),]
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table(comp_lin_all$lineage); sum(table(comp_lin_all$lineage))
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df3_actual = df3[!is.na(df3$dst), ]
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table(df3_actual$dst_mode)
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comp_lin_actual = df3_actual[df3_actual$lineage_labels%in%c("L1", "L2", "L3", "L4"),]
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table(comp_lin_actual$lineage); sum(table(comp_lin_actual$lineage))
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# df3_complete = df3
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# table(df3_complete$dst_mode)
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# comp_lin_all = df3_complete[df3_complete$lineage_labels%in%c("L1", "L2", "L3", "L4"),]
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# table(comp_lin_all$lineage); sum(table(comp_lin_all$lineage))
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#
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# df3_actual = df3[!is.na(df3$dst), ]
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# table(df3_actual$dst_mode)
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# comp_lin_actual = df3_actual[df3_actual$lineage_labels%in%c("L1", "L2", "L3", "L4"),]
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# table(comp_lin_actual$lineage); sum(table(comp_lin_actual$lineage))
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#
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260
scripts/count_vars_ML_v1.R
Normal file
260
scripts/count_vars_ML_v1.R
Normal file
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@ -0,0 +1,260 @@
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# count numbers for ML
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source("~/git/LSHTM_analysis/config/alr.R")
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#source("~/git/LSHTM_analysis/config/embb.R")
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#source("~/git/LSHTM_analysis/config/gid.R")
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#source("~/git/LSHTM_analysis/config/katg.R")
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#source("~/git/LSHTM_analysis/config/pnca.R")
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#source("~/git/LSHTM_analysis/config/rpob.R")
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#############################
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# GET the actual merged dfs
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#############################
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source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
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#############################
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# Output files: merged data
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#############################
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outfile_merged_df3 = paste0(outdir, '/', tolower(gene), '_merged_df3.csv')
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#outfile_merged_df2 = paste0(outdir, '/', tolower(gene), '_merged_df2.csv')
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################################################
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# Add acticve site indication
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###############################################
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merged_df2$active_site = as.integer(merged_df2$position %in% active_aa_pos)
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#merged_df2_comp$active_site = as.integer(merged_df2_comp$position %in% active_aa_pos)
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merged_df3$active_site = as.integer(merged_df3$position %in% active_aa_pos)
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#merged_df3_comp$active_site = as.integer(merged_df3_comp$position %in% active_aa_pos)
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# check
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cols_sel = c('mutationinformation', 'mutation_info_labels'
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#, 'dm_om_numeric'
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, 'dst', 'dst_mode')
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check_mdf2 = merged_df2[, cols_sel]
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check_mdf2T = table(check_mdf2$mutationinformation, check_mdf2$dst_mode)
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ft_mdf2 = as.data.frame.matrix(check_mdf2T)
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#==================
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# CHECK: dst mode
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#===================
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dst_check = all((ft_mdf2[,1]==0)==(ft_mdf2[,2]!=0)); dst_check
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#=======================
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# CHECK: dst mode labels
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#=======================
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table(merged_df2$mutation_info_labels_orig)
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table(merged_df2$mutation_info_labels_v1)
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table(merged_df2$mutation_info_labels)
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dst_check1 = table(merged_df2$dst_mode)[1] == table(merged_df2$mutation_info_labels)[2]
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dst_check2 = table(merged_df2$dst_mode)[2] == table(merged_df2$mutation_info_labels)[1]
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check12 = all(dst_check && all(dst_check1 == dst_check2))
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if (check12) {
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cat('\nPASS: dst mode labels verified. merged_df3 CAN be trusted! ')
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}else{
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stop('FAIL: Something is wrong with the dst_mode column. Quitting!')
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}
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table(is.na(merged_df3$dst))
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#==========================
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# CHECK: active site labels
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#==========================
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table(merged_df2$active_site)
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table(merged_df3$active_site)
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aa_check1 = all( table(merged_df2$active_site) == table(as.integer(merged_df2$position %in% active_aa_pos)) )
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aa_check2 = all( table(merged_df3$active_site) == table(as.integer(merged_df3$position %in% active_aa_pos)) )
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if ( all(aa_check1 && aa_check2) ){
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cat('\nActive site indications successfully applied to merged_dfs for gene:', tolower(gene))
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}
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gene
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gene_match
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nrow(merged_df3)
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###########################################
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#========================
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# CHECK: drtype: revised labels [Merged_df2]
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#=========================
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table(merged_df2$drtype) #orig
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table(merged_df2$drtype_mode)
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# mapping 2.1: numeric
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# drtype_map = {'XDR': 5
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# , 'Pre-XDR': 4
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# , 'MDR': 3
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# , 'Pre-MDR': 2
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# , 'Other': 1
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# , 'Sensitive': 0}
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# create a labels col that is mapped based on drtype_mode
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merged_df2$drtype_mode_labels = merged_df2$drtype_mode
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merged_df2$drtype_mode_labels = as.factor(merged_df2$drtype_mode)
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levels(merged_df2$drtype_mode_labels)
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levels(merged_df2$drtype_mode_labels) <- c('Sensitive', 'Other'
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, 'Pre-MDR', 'MDR'
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, 'Pre-XDR', 'XDR')
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levels(merged_df2$drtype_mode_labels)
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# check
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a1 = all(table(merged_df2$drtype_mode) == table(merged_df2$drtype_mode_labels))
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b1 = sum(table(merged_df2$drtype_mode_labels)) == nrow(merged_df2)
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if (all(a1 && b1)){
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cat("\nPASS: added drtype mode labels to merged_df2")
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}else{
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stop("FAIL: could not add drtype mode labels to merged_df2")
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##quit()
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}
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#################################################
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#=======================
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# CHECK: drtype: revised labels [merged_df3]
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#=======================
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table(merged_df3$drtype) #orig
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table(merged_df3$drtype_mode)
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# mapping 2.1: numeric
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# drtype_map = {'XDR': 5
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# , 'Pre-XDR': 4
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# , 'MDR': 3
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# , 'Pre-MDR': 2
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# , 'Other': 1
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# , 'Sensitive': 0}
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# create a labels col that is mapped based on drtype_mode
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merged_df3$drtype_mode_labels = merged_df3$drtype_mode
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merged_df3$drtype_mode_labels = as.factor(merged_df3$drtype_mode)
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levels(merged_df3$drtype_mode_labels)
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levels(merged_df3$drtype_mode_labels) <- c('Sensitive', 'Other'
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, 'Pre-MDR', 'MDR'
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, 'Pre-XDR', 'XDR')
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levels(merged_df3$drtype_mode_labels)
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a2 = all(table(merged_df3$drtype_mode) == table(merged_df3$drtype_mode_labels))
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b2 = sum(table(merged_df3$drtype_mode_labels)) == nrow(merged_df3)
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# check
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if (all(a2 && b2)){
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cat("\nPASS: added drtype mode labels to merged_df3")
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}else{
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stop("FAIL: could not add drtype mode labels to merged_df3")
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##quit()
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}
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#===============
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# CHECK: lineage
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#===============
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l1 = table(merged_df3$lineage) == table(merged_df3$lineage_labels)
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l2 = table(merged_df2$lineage) == table(merged_df2$lineage_labels)
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l3 = sum(table(merged_df2$lineage_labels)) == nrow(merged_df2)
|
||||
l4 = sum(table(merged_df3$lineage_labels)) == nrow(merged_df3)
|
||||
|
||||
if (all(l1 && l2 && l3 && l4) ){
|
||||
cat("\nPASS: lineage and lineage labels are identical!")
|
||||
}else{
|
||||
stop("FAIL: could not verify lineage labels")
|
||||
##quit()
|
||||
}
|
||||
|
||||
###############################################
|
||||
# #=============
|
||||
# # mutation_info: revised labels
|
||||
# #==============
|
||||
# table(merged_df3$mutation_info)
|
||||
# sum(table(merged_df3$mutation_info))
|
||||
# table(merged_df3$mutation_info_orig)
|
||||
##############################################
|
||||
|
||||
# #=============
|
||||
# # <drug>, dst_mode: revised labels
|
||||
# #==============
|
||||
# table(merged_df3$dst) # orig
|
||||
# sum(table(merged_df3$dst))
|
||||
#
|
||||
# table(merged_df3$dst_mode)
|
||||
# #table(merged_df3[dr_muts_col])
|
||||
# sum(table(merged_df3$drtype_mode))
|
||||
|
||||
##############################################
|
||||
if ( all( check12 && aa_check1 && aa_check2 && a1 && b1 && a2 && b2 && l1 && l2 && l3 && l4) ){
|
||||
cat("\nWriting merged_dfs for:"
|
||||
, "\nDrug:", drug
|
||||
, "\nGene:", gene)
|
||||
|
||||
write.csv(merged_df3, outfile_merged_df3)
|
||||
#write.csv(merged_df2, outfile_merged_df2)
|
||||
|
||||
cat(paste("\nmerged df3 filename:", outfile_merged_df3
|
||||
#, "\nmerged df2 filename:", outfile_merged_df2)
|
||||
))
|
||||
|
||||
} else{
|
||||
stop("FAIL: Not able to write merged dfs. Please check numbers!")
|
||||
#quit()
|
||||
}
|
||||
|
||||
#%%###################################################################
|
||||
# check merged_df3
|
||||
check_mdf3 = merged_df3[, cols_sel]
|
||||
|
||||
check_mdf3T = table(check_mdf3$mutationinformation, check_mdf3$dst_mode)
|
||||
ft_mdf3 = as.data.frame.matrix(check_mdf3T)
|
||||
|
||||
#==================
|
||||
# CHECK: dst mode
|
||||
#===================
|
||||
dst_check_mdf3 = all((ft_mdf3[,1]==0)==(ft_mdf3[,2]!=0)); dst_check_mdf3
|
||||
|
||||
sel = c("mutationinformation", "dst", "dst_mode")
|
||||
|
||||
a = merged_df3[, sel]
|
||||
str(a)
|
||||
|
||||
|
||||
###################################################
|
||||
###################################################
|
||||
###################################################
|
||||
|
||||
source("~/git/LSHTM_analysis/config/alr.R")
|
||||
source("~/git/LSHTM_analysis/config/embb.R")
|
||||
source("~/git/LSHTM_analysis/config/gid.R")
|
||||
source("~/git/LSHTM_analysis/config/katg.R")
|
||||
source("~/git/LSHTM_analysis/config/pnca.R")
|
||||
source("~/git/LSHTM_analysis/config/rpob.R")
|
||||
#
|
||||
df3_filename = paste0("/home/tanu/git/Data/", drug, "/output/", tolower(gene), "_merged_df3.csv")
|
||||
df3 = read.csv(df3_filename)
|
||||
#
|
||||
# mutationinformation
|
||||
length(unique((df3$mutationinformation)))
|
||||
#
|
||||
# #dm _om
|
||||
table(df3$mutation_info)
|
||||
table(df3$mutation_info_orig)
|
||||
table(df3$mutation_info_labels_orig)
|
||||
|
||||
# used in plots and analyses
|
||||
table(df3$mutation_info_labels) # different, and matches dst_mode
|
||||
table(df3$dst_mode)
|
||||
|
||||
# test_set
|
||||
na_count <-sapply(df3, function(y) sum(length(which(is.na(y)))))
|
||||
na_count[drug]
|
||||
#
|
||||
# # training set
|
||||
table(df3[drug])
|
||||
#
|
||||
# # drtype: MDR and XDR
|
||||
# #table(df3$drtype) orig i.e. incorrect ones!
|
||||
# table(df3$drtype_mode_labels)
|
||||
|
||||
|
||||
df3_complete = df3
|
||||
table(df3_complete$dst_mode)
|
||||
comp_lin_all = df3_complete[df3_complete$lineage_labels%in%c("L1", "L2", "L3", "L4"),]
|
||||
table(comp_lin_all$lineage); sum(table(comp_lin_all$lineage))
|
||||
|
||||
df3_actual = df3[!is.na(df3$dst), ]
|
||||
table(df3_actual$dst_mode)
|
||||
comp_lin_actual = df3_actual[df3_actual$lineage_labels%in%c("L1", "L2", "L3", "L4"),]
|
||||
table(comp_lin_actual$lineage); sum(table(comp_lin_actual$lineage))
|
||||
|
|
@ -1,12 +1,13 @@
|
|||
source("~/git/LSHTM_analysis/config/alr.R")
|
||||
source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
||||
source("~/git/LSHTM_analysis/scripts/plotting/plotting_colnames.R")
|
||||
|
||||
#=======
|
||||
# output
|
||||
#=======
|
||||
outdir_images = paste0("~/git/Writing/thesis/images/results/", tolower(gene), "/")
|
||||
#outdir_images = paste0("/home/pub/Work/LSHTM/Thesis_Plots/pairs/")
|
||||
#cat("plots will output to:", outdir_images)
|
||||
|
||||
cat("plots will output to:", outdir_images)
|
||||
|
||||
custom_cor <- function(
|
||||
data,
|
||||
|
|
@ -190,7 +191,7 @@ unmasked_vals
|
|||
# Stability
|
||||
#================
|
||||
corr_ps_colnames = c(static_cols
|
||||
, "DUET"
|
||||
, "mCSM-DUET"
|
||||
, "FoldX"
|
||||
, "DeepDDG"
|
||||
, "Dynamut2"
|
||||
|
|
|
|||
|
|
@ -7,8 +7,8 @@
|
|||
#=============
|
||||
# Data: Input
|
||||
#==============
|
||||
#source("~/git/LSHTM_analysis/config/embb.R")
|
||||
#source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
||||
source("~/git/LSHTM_analysis/config/embb.R")
|
||||
source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
||||
|
||||
#cat("\nSourced plotting cols as well:", length(plotting_cols))
|
||||
|
||||
|
|
|
|||
|
|
@ -1,5 +1,4 @@
|
|||
#source("~/git/LSHTM_analysis/config/embb.R")
|
||||
#source("~/git/LSHTM_analysis/scripts/plotting/plotting_colnames.R")
|
||||
#source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
||||
|
||||
my_gg_pairs=function(plot_df, plot_title
|
||||
|
|
@ -53,7 +52,7 @@ corr_plotdf = corr_data_extract(merged_df3
|
|||
|
||||
aff_dist_cols = colnames(corr_plotdf)[grep("Dist", colnames(corr_plotdf))]
|
||||
static_cols = c("Log10(MAF)"
|
||||
, "Log10(OR)"
|
||||
#, "Log10(OR)"
|
||||
)
|
||||
############################################################
|
||||
#=============================================
|
||||
|
|
@ -85,7 +84,7 @@ unmasked_vals
|
|||
# Stability
|
||||
#================
|
||||
corr_ps_colnames = c(static_cols
|
||||
, "DUET"
|
||||
, "mCSM-DUET"
|
||||
, "FoldX"
|
||||
, "DeepDDG"
|
||||
, "Dynamut2"
|
||||
|
|
|
|||
|
|
@ -95,7 +95,7 @@ unmasked_vals
|
|||
# Stability
|
||||
#================
|
||||
corr_ps_colnames = c(static_cols
|
||||
, "DUET"
|
||||
, "mCSM-DUET"
|
||||
, "FoldX"
|
||||
, "DeepDDG"
|
||||
, "Dynamut2"
|
||||
|
|
|
|||
|
|
@ -1,6 +1,13 @@
|
|||
#source("~/git/LSHTM_analysis/config/katg.R")
|
||||
#source("~/git/LSHTM_analysis/scripts/plotting/plotting_colnames.R")
|
||||
#source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
||||
source("~/git/LSHTM_analysis/config/katg.R")
|
||||
source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
||||
|
||||
#=======
|
||||
# output
|
||||
#=======
|
||||
outdir_images = paste0("~/git/Writing/thesis/images/results/", tolower(gene), "/")
|
||||
cat("plots will output to:", outdir_images)
|
||||
|
||||
|
||||
|
||||
my_gg_pairs=function(plot_df, plot_title
|
||||
, tt_args_size = 2.5
|
||||
|
|
@ -85,7 +92,7 @@ unmasked_vals
|
|||
# Stability
|
||||
#================
|
||||
corr_ps_colnames = c(static_cols
|
||||
, "DUET"
|
||||
, "mCSM-DUET"
|
||||
, "FoldX"
|
||||
, "DeepDDG"
|
||||
, "Dynamut2"
|
||||
|
|
|
|||
|
|
@ -203,6 +203,14 @@ write.csv(bar_or, paste0(outdir_stats, "katg_OR_10.csv"))
|
|||
top10_or$position[top10_or$position%in%active_aa_pos]
|
||||
|
||||
|
||||
# maf
|
||||
bar_maf = bar_or[order(bar_or$maf_percent
|
||||
, bar_or$ligand_distance
|
||||
# bar_or$nca_dist
|
||||
, bar_or$interface_dist
|
||||
, decreasing = T), ]
|
||||
|
||||
head(bar_maf)
|
||||
#########################################################
|
||||
# closest most sig
|
||||
bar_or_lig = bar_or[bar_or$ligand_distance<10,]
|
||||
|
|
|
|||
|
|
@ -7,10 +7,10 @@
|
|||
#=============
|
||||
# Data: Input
|
||||
#==============
|
||||
#source("~/git/LSHTM_analysis/config/rpob.R")
|
||||
#source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
||||
source("~/git/LSHTM_analysis/config/rpob.R")
|
||||
source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
||||
|
||||
#cat("\nSourced plotting cols as well:", length(plotting_cols))
|
||||
cat("\nSourced plotting cols as well:", length(plotting_cols))
|
||||
|
||||
####################################################
|
||||
class(merged_df3)
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue