reran to output merged_df3 and merged_df2 csvs from count_vars.ML
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1 changed files with 33 additions and 33 deletions
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@ -4,7 +4,7 @@
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#source("~/git/LSHTM_analysis/config/embb.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/gid.R")
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#source("~/git/LSHTM_analysis/config/katg.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/pnca.R")
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#source("~/git/LSHTM_analysis/config/rpob.R")
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#source("~/git/LSHTM_analysis/config/rpob.R")
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source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
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source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
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@ -80,35 +80,35 @@ write.csv(merged_df2, outfile_merged_df2)
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###################################################
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###################################################
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###################################################
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###################################################
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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/alr.R")
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source("~/git/LSHTM_analysis/config/embb.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/gid.R")
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source("~/git/LSHTM_analysis/config/katg.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/pnca.R")
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source("~/git/LSHTM_analysis/config/rpob.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_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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# df3 = read.csv(df3_filename)
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#
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# mutationinformation
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# # mutationinformation
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length(unique((df3$mutationinformation)))
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# length(unique((df3$mutationinformation)))
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#
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#dm _om
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# #dm _om
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table(df3$mutation_info)
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# table(df3$mutation_info)
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table(df3$mutation_info_labels)
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# table(df3$mutation_info_labels)
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table(df3$mutation_info_orig)
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# table(df3$mutation_info_orig)
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table(df3$mutation_info_labels_orig)
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# table(df3$mutation_info_labels_orig)
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#
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# test_set
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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 <-sapply(df3, function(y) sum(length(which(is.na(y)))))
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na_count[drug]
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# na_count[drug]
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#
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# training set
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# # training set
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table(df3[drug])
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# table(df3[drug])
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#
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# drtype: MDR and XDR
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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) orig i.e. incorrect ones!
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table(df3$drtype_mode_labels)
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# table(df3$drtype_mode_labels)
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#
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#
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