LSHTM_analysis/scripts/count_vars_ML.R

135 lines
4.5 KiB
R

# count numbers for ML
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")
#############################
# GET the actual merged dfs
#############################
#source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
source("~/git/LSHTM_analysis/scripts/plotting/get_ml_dfs.R")
#############################
# Output files: merged data
#############################
outfile_merged_df3 = paste0(outdir, '/', tolower(gene), '_merged_df3.csv')
#outfile_merged_df2 = paste0(outdir, '/', tolower(gene), '_merged_df2.csv')
################################################
# Add acticve site indication
###############################################
merged_df2$active_site = as.integer(merged_df2$position %in% active_aa_pos)
merged_df3$active_site = as.integer(merged_df3$position %in% active_aa_pos)
# check
cols_sel = c('mutationinformation', 'mutation_info_labels'
#, 'dm_om_numeric'
, 'dst', 'dst_mode')
check_mdf2 = merged_df2[, cols_sel]
check_mdf2T = table(check_mdf2$mutationinformation, check_mdf2$dst_mode)
ft_mdf2 = as.data.frame.matrix(check_mdf2T)
#==================
# CHECK: dst mode
#===================
dst_check = all((ft_mdf2[,1]==0)==(ft_mdf2[,2]!=0)); dst_check
#=======================
# CHECK: dst mode labels
#=======================
#table(merged_df2$mutation_info_labels_orig)
#table(merged_df2$mutation_info_labels_v1)
table(merged_df2$mutation_info_labels)
dst_check1 = table(merged_df2$dst_mode)[1] == table(merged_df2$mutation_info_labels)[2]
dst_check2 = table(merged_df2$dst_mode)[2] == table(merged_df2$mutation_info_labels)[1]
check12 = all(dst_check && all(dst_check1 == dst_check2))
if (check12) {
cat('\nPASS: dst mode labels verified. merged_df3 CAN be trusted! ')
}else{
stop('FAIL: Something is wrong with the dst_mode column. Quitting!')
}
table(is.na(merged_df3$dst))
#==========================
# CHECK: active site labels
#==========================
table(merged_df2$active_site)
table(merged_df3$active_site)
aa_check1 = all( table(merged_df2$active_site) == table(as.integer(merged_df2$position %in% active_aa_pos)) )
aa_check2 = all( table(merged_df3$active_site) == table(as.integer(merged_df3$position %in% active_aa_pos)) )
if ( all(aa_check1 && aa_check2) ){
cat('\nActive site indications successfully applied to merged_dfs for gene:', tolower(gene))
}
gene
gene_match
nrow(merged_df3)
##############################################
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)
))
#%%###################################################################
###################################################
###################################################
###################################################
# 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("~/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))
#