a massive waste of time
This commit is contained in:
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3 changed files with 726 additions and 620 deletions
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@ -1,14 +1,14 @@
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#!/usr/bin/env Rscript
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#########################################################
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# TASK: Script to format data for dm om plots:
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# generating WF and LF data for each of the parameters:
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# duet, mcsm-lig, foldx, deepddg, dynamut2, mcsm-na, mcsm-ppi2, encom, dynamut..etc
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# Called by get_plotting_dfs.R
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# generating WF and LF data for each of the parameters:
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# duet, mcsm-lig, foldx, deepddg, dynamut2, mcsm-na, mcsm-ppi2, encom, dynamut..etc
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# Called by get_plotting_dfs.R
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##################################################################
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# from plotting_globals.R
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# DistCutOff, LigDist_colname, ppi2Dist_colname, naDist_colname
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gene
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#gene
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dm_om_wf_lf_data <- function(df
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, gene # from globals
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@ -28,9 +28,15 @@ dm_om_wf_lf_data <- function(df
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sum(is.na(df$maf2))
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# Initialise the required dfs based on gene name
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#geneL_normal = c("pnca")
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#geneL_na = c("gid", "rpob")
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#geneL_ppi2 = c("alr", "embb", "katg", "rpob")
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#ADDED: IMPORTANT for rpob to be in both to make sure all data is returned
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geneL_normal = c("pnca")
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geneL_na = c("gid", "rpob")
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geneL_ppi2 = c("alr", "embb", "katg", "rpob")
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geneL_both = c("rpob")
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geneL_ppi2 = c("alr", "embb", "katg")
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geneL_na = c("gid")
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# common_dfs
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common_dfsL = list(
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@ -59,6 +65,14 @@ dm_om_wf_lf_data <- function(df
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wf_lf_dataL = common_dfsL
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}
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if (tolower(gene)%in%geneL_ppi2){
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additional_dfL = list(
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wf_mcsm_ppi2 = data.frame()
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, lf_mcsm_ppi2 = data.frame()
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)
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wf_lf_dataL = c(common_dfsL, additional_dfL)
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}
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if (tolower(gene)%in%geneL_na){
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additional_dfL = list(
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wf_mcsm_na = data.frame()
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@ -67,13 +81,16 @@ dm_om_wf_lf_data <- function(df
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wf_lf_dataL = c(common_dfsL, additional_dfL)
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}
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if (tolower(gene)%in%geneL_ppi2){
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if (tolower(gene)%in%geneL_both){
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additional_dfL = list(
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wf_mcsm_ppi2 = data.frame()
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, lf_mcsm_ppi2 = data.frame()
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wf_mcsm_ppi2 = data.frame(),
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lf_mcsm_ppi2 = data.frame(),
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wf_mcsm_na = data.frame(),
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lf_mcsm_na = data.frame()
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)
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wf_lf_dataL = c(common_dfsL, additional_dfL)
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}
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cat("\nInitializing an empty list of length:"
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, length(wf_lf_dataL))
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@ -237,454 +254,486 @@ dm_om_wf_lf_data <- function(df
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}
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if (tolower(gene)%in%geneL_both){
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colnames_to_extract = c(
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common_colnames,
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"mcsm_ppi2_affinity" ,
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"mcsm_ppi2_scaled" ,
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"mcsm_ppi2_outcome" ,
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ppi2Dist_colname,
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"mcsm_na_affinity" ,
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"mcsm_na_scaled" ,
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"mcsm_na_outcome" ,
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naDist_colname
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)
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display_colnames = c(
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display_common_colnames,
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"mcsm_ppi2_affinity",
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mcsm_ppi2_dn,
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"mcsm_ppi2_outcome",
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ppi2_dist_dn,
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"mcsm_na_affinity",
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mcsm_na_dn,
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"mcsm_na_outcome",
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na_dist_dn
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)
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comb_df_sl = df[, colnames_to_extract]
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colnames(comb_df_sl) = display_colnames
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comb_df_sl_ppi2 = comb_df_sl[comb_df_sl[[ppi2_dist_dn]]<DistCutOff,]
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comb_df_sl_na = comb_df_sl[comb_df_sl[[na_dist_dn]]<DistCutOff,]
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static_cols_end = c(na_dist_dn, static_cols_end_common)
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}
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# Affinity filtered data: mcsm-lig: COMMON for all genes, mcsm-lig --> LigDist_colname
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comb_df_sl_lig = comb_df_sl[comb_df_sl[[lig_dist_dn]]<DistCutOff,]
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}
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#======================
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# Selecting dfs
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# with appropriate cols
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#=======================
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static_cols_start = c(snp_colname
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#======================
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# Selecting dfs
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# with appropriate cols
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#=======================
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static_cols_start = c(snp_colname
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, aa_pos_colname
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, mut_colname
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, mut_info_label_colname)
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# static_cols_end
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cat("\nEnd colnames for gene:", static_cols_end)
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# static_cols_end
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cat("\nEnd colnames for gene:", static_cols_end)
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#########################################################################
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#==============
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# Distance and genomics
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#==============
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# WF data: dist + genomics
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cols_to_select_dist_gen = c(static_cols_start, c("duet_outcome", duet_dn), static_cols_end)
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wf_dist_gen = comb_df_sl[, cols_to_select_dist_gen]; head(wf_dist_gen)
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#########################################################################
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#==============
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# Distance and genomics
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#==============
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# WF data: dist + genomics
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cols_to_select_dist_gen = c(static_cols_start, c("duet_outcome", duet_dn), static_cols_end)
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wf_dist_gen = comb_df_sl[, cols_to_select_dist_gen]; head(wf_dist_gen)
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#pivot_cols_ps = cols_to_select_ps[1:5]; pivot_cols_ps
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pivot_cols_dist_gen = cols_to_select_dist_gen[1: (length(static_cols_start) + 1)]; pivot_cols_dist_gen
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expected_rows_lf = nrow(wf_dist_gen) * (length(wf_dist_gen) - length(pivot_cols_dist_gen))
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expected_rows_lf
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#pivot_cols_ps = cols_to_select_ps[1:5]; pivot_cols_ps
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pivot_cols_dist_gen = cols_to_select_dist_gen[1: (length(static_cols_start) + 1)]; pivot_cols_dist_gen
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expected_rows_lf = nrow(wf_dist_gen) * (length(wf_dist_gen) - length(pivot_cols_dist_gen))
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expected_rows_lf
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# LF dist and genomics
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lf_dist_gen = tidyr::gather(wf_dist_gen
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# LF dist and genomics
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lf_dist_gen = tidyr::gather(wf_dist_gen
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, key = param_type
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, value = param_value
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, all_of(duet_dn):tail(static_cols_end,1)
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, factor_key = TRUE)
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if (nrow(lf_dist_gen) == expected_rows_lf){
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if (nrow(lf_dist_gen) == expected_rows_lf){
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cat("\nPASS: long format data created for Distance and Genomics")
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}else{
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}else{
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cat("\nFAIL: long format data could not be created for Distance and Genomics")
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quit()
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}
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}
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# DROP duet cols
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drop_cols = c(duet_dn, "duet_outcome"); drop_cols
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table(lf_dist_gen$param_type)
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lf_dist_gen = lf_dist_gen[!lf_dist_gen$param_type%in%drop_cols,]
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lf_dist_gen$param_type = factor(lf_dist_gen$param_type)
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table(lf_dist_gen$param_type)
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# DROP duet cols
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drop_cols = c(duet_dn, "duet_outcome"); drop_cols
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table(lf_dist_gen$param_type)
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lf_dist_gen = lf_dist_gen[!lf_dist_gen$param_type%in%drop_cols,]
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lf_dist_gen$param_type = factor(lf_dist_gen$param_type)
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table(lf_dist_gen$param_type)
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# NEW columns [outcome and outcome colname]
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lf_dist_gen$outcome_colname = mut_info_colname
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lf_dist_gen$outcome = lf_dist_gen[[mut_info_label_colname]]
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head(lf_dist_gen)
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# NEW columns [outcome and outcome colname]
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lf_dist_gen$outcome_colname = mut_info_colname
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lf_dist_gen$outcome = lf_dist_gen[[mut_info_label_colname]]
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head(lf_dist_gen)
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wf_dist_gen = subset(wf_dist_gen, select = !(names(wf_dist_gen) %in% drop_cols))
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wf_dist_gen = subset(wf_dist_gen, select = !(names(wf_dist_gen) %in% drop_cols))
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colnames(wf_dist_gen)
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colnames(lf_dist_gen)
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colnames(wf_dist_gen)
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colnames(lf_dist_gen)
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# Assign them to the output list
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wf_lf_dataL[['wf_dist_gen']] = wf_dist_gen
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wf_lf_dataL[['lf_dist_gen']] = lf_dist_gen
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##########################################################
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# Assign them to the output list
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wf_lf_dataL[['wf_dist_gen']] = wf_dist_gen
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wf_lf_dataL[['lf_dist_gen']] = lf_dist_gen
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##########################################################
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#==============
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# DUET
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#==============
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# WF data: duet
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cols_to_select_duet = c(static_cols_start, c("duet_outcome", duet_dn), static_cols_end)
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wf_duet = comb_df_sl[, cols_to_select_duet]
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#==============
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# DUET
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#==============
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# WF data: duet
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cols_to_select_duet = c(static_cols_start, c("duet_outcome", duet_dn), static_cols_end)
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wf_duet = comb_df_sl[, cols_to_select_duet]
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#pivot_cols_ps = cols_to_select_ps[1:5]; pivot_cols_ps
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pivot_cols_duet = cols_to_select_duet[1: (length(static_cols_start) + 1)]; pivot_cols_duet
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expected_rows_lf = nrow(wf_duet) * (length(wf_duet) - length(pivot_cols_duet))
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expected_rows_lf
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#pivot_cols_ps = cols_to_select_ps[1:5]; pivot_cols_ps
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pivot_cols_duet = cols_to_select_duet[1: (length(static_cols_start) + 1)]; pivot_cols_duet
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expected_rows_lf = nrow(wf_duet) * (length(wf_duet) - length(pivot_cols_duet))
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expected_rows_lf
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# LF data: duet
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lf_duet = tidyr::gather(wf_duet
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# LF data: duet
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lf_duet = tidyr::gather(wf_duet
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, key = param_type
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, value = param_value
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, all_of(duet_dn):tail(static_cols_end,1)
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, factor_key = TRUE)
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if (nrow(lf_duet) == expected_rows_lf){
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if (nrow(lf_duet) == expected_rows_lf){
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cat("\nPASS: long format data created for ", duet_dn)
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}else{
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}else{
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cat("\nFAIL: long format data could not be created for duet")
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quit()
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}
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}
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table(lf_duet$param_type)
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table(lf_duet$param_type)
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# NEW columns [outcome and outcome colname]
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lf_duet$outcome_colname = "duet_outcome"
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lf_duet$outcome = lf_duet$duet_outcome
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# NEW columns [outcome and outcome colname]
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lf_duet$outcome_colname = "duet_outcome"
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lf_duet$outcome = lf_duet$duet_outcome
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# DROP static cols
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lf_duet = lf_duet[!lf_duet$param_type%in%c(static_cols_end),]
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lf_duet$param_type = factor(lf_duet$param_type)
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table(lf_duet$param_type); colnames(lf_duet)
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# DROP static cols
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lf_duet = lf_duet[!lf_duet$param_type%in%c(static_cols_end),]
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lf_duet$param_type = factor(lf_duet$param_type)
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table(lf_duet$param_type); colnames(lf_duet)
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# Assign them to the output list
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wf_lf_dataL[['wf_duet']] = wf_duet
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wf_lf_dataL[['lf_duet']] = lf_duet
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# Assign them to the output list
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wf_lf_dataL[['wf_duet']] = wf_duet
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wf_lf_dataL[['lf_duet']] = lf_duet
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############################################################################
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#==============
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# FoldX
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#==============
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# WF data: Foldx
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cols_to_select_foldx= c(static_cols_start, c("foldx_outcome", foldx_dn), static_cols_end)
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wf_foldx = comb_df_sl[, cols_to_select_foldx]
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############################################################################
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#==============
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# FoldX
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#==============
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# WF data: Foldx
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cols_to_select_foldx= c(static_cols_start, c("foldx_outcome", foldx_dn), static_cols_end)
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wf_foldx = comb_df_sl[, cols_to_select_foldx]
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pivot_cols_foldx = cols_to_select_foldx[1: (length(static_cols_start) + 1)]; pivot_cols_foldx
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expected_rows_lf = nrow(wf_foldx) * (length(wf_foldx) - length(pivot_cols_foldx))
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expected_rows_lf
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pivot_cols_foldx = cols_to_select_foldx[1: (length(static_cols_start) + 1)]; pivot_cols_foldx
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expected_rows_lf = nrow(wf_foldx) * (length(wf_foldx) - length(pivot_cols_foldx))
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expected_rows_lf
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# LF data: Foldx
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lf_foldx = gather(wf_foldx
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# LF data: Foldx
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lf_foldx = gather(wf_foldx
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, key = param_type
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, value = param_value
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, all_of(foldx_dn):tail(static_cols_end,1)
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, factor_key = TRUE)
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if (nrow(lf_foldx) == expected_rows_lf){
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if (nrow(lf_foldx) == expected_rows_lf){
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cat("\nPASS: long format data created for ", foldx_dn)
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}else{
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}else{
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cat("\nFAIL: long format data could not be created for duet")
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quit()
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}
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}
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# NEW column
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lf_foldx$outcome_colname = "foldx_outcome"
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lf_foldx$outcome = lf_foldx$foldx_outcome
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# NEW column
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lf_foldx$outcome_colname = "foldx_outcome"
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lf_foldx$outcome = lf_foldx$foldx_outcome
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# DROP static cols
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lf_foldx = lf_foldx[!lf_foldx$param_type%in%c(static_cols_end),]
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lf_foldx$param_type = factor(lf_foldx$param_type)
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table(lf_foldx$param_type); colnames(lf_foldx)
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# DROP static cols
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lf_foldx = lf_foldx[!lf_foldx$param_type%in%c(static_cols_end),]
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lf_foldx$param_type = factor(lf_foldx$param_type)
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table(lf_foldx$param_type); colnames(lf_foldx)
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# Assign them to the output list
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wf_lf_dataL[['wf_foldx']] = wf_foldx
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wf_lf_dataL[['lf_foldx']] = lf_foldx
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# Assign them to the output list
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wf_lf_dataL[['wf_foldx']] = wf_foldx
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wf_lf_dataL[['lf_foldx']] = lf_foldx
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############################################################################
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#==============
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# Deepddg
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#==============
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# WF data: deepddg
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cols_to_select_deepddg = c(static_cols_start, c("deepddg_outcome", deepddg_dn), static_cols_end)
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wf_deepddg = comb_df_sl[, cols_to_select_deepddg]
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############################################################################
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#==============
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# Deepddg
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#==============
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# WF data: deepddg
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cols_to_select_deepddg = c(static_cols_start, c("deepddg_outcome", deepddg_dn), static_cols_end)
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wf_deepddg = comb_df_sl[, cols_to_select_deepddg]
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pivot_cols_deepddg = cols_to_select_deepddg[1: (length(static_cols_start) + 1)]; pivot_cols_deepddg
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expected_rows_lf = nrow(wf_deepddg) * (length(wf_deepddg) - length(pivot_cols_deepddg))
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expected_rows_lf
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pivot_cols_deepddg = cols_to_select_deepddg[1: (length(static_cols_start) + 1)]; pivot_cols_deepddg
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expected_rows_lf = nrow(wf_deepddg) * (length(wf_deepddg) - length(pivot_cols_deepddg))
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expected_rows_lf
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# LF data: Deepddg
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lf_deepddg = gather(wf_deepddg
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# LF data: Deepddg
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lf_deepddg = gather(wf_deepddg
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, key = param_type
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, value = param_value
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, all_of(deepddg_dn):tail(static_cols_end,1)
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, factor_key = TRUE)
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if (nrow(lf_deepddg) == expected_rows_lf){
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if (nrow(lf_deepddg) == expected_rows_lf){
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cat("\nPASS: long format data created for ", deepddg_dn)
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}else{
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}else{
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cat("\nFAIL: long format data could not be created for duet")
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quit()
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}
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}
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# NEW columns [outcome and outcome colname]
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lf_deepddg$outcome_colname = "deepddg_outcome"
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lf_deepddg$outcome = lf_deepddg$deepddg_outcome
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# NEW columns [outcome and outcome colname]
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lf_deepddg$outcome_colname = "deepddg_outcome"
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lf_deepddg$outcome = lf_deepddg$deepddg_outcome
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||||
|
||||
# DROP static cols
|
||||
lf_deepddg = lf_deepddg[!lf_deepddg$param_type%in%c(static_cols_end),]
|
||||
lf_deepddg$param_type = factor(lf_deepddg$param_type)
|
||||
table(lf_deepddg$param_type); colnames(lf_deepddg)
|
||||
# DROP static cols
|
||||
lf_deepddg = lf_deepddg[!lf_deepddg$param_type%in%c(static_cols_end),]
|
||||
lf_deepddg$param_type = factor(lf_deepddg$param_type)
|
||||
table(lf_deepddg$param_type); colnames(lf_deepddg)
|
||||
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_deepddg']] = wf_deepddg
|
||||
wf_lf_dataL[['lf_deepddg']] = lf_deepddg
|
||||
############################################################################
|
||||
#==============
|
||||
# Dynamut2: LF
|
||||
#==============
|
||||
# WF data: dynamut2
|
||||
cols_to_select_dynamut2 = c(static_cols_start, c("ddg_dynamut2_outcome", dynamut2_dn), static_cols_end)
|
||||
wf_dynamut2 = comb_df_sl[, cols_to_select_dynamut2]
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_deepddg']] = wf_deepddg
|
||||
wf_lf_dataL[['lf_deepddg']] = lf_deepddg
|
||||
############################################################################
|
||||
#==============
|
||||
# Dynamut2: LF
|
||||
#==============
|
||||
# WF data: dynamut2
|
||||
cols_to_select_dynamut2 = c(static_cols_start, c("ddg_dynamut2_outcome", dynamut2_dn), static_cols_end)
|
||||
wf_dynamut2 = comb_df_sl[, cols_to_select_dynamut2]
|
||||
|
||||
pivot_cols_dynamut2 = cols_to_select_dynamut2[1: (length(static_cols_start) + 1)]; pivot_cols_dynamut2
|
||||
expected_rows_lf = nrow(wf_dynamut2) * (length(wf_dynamut2) - length(pivot_cols_dynamut2))
|
||||
expected_rows_lf
|
||||
pivot_cols_dynamut2 = cols_to_select_dynamut2[1: (length(static_cols_start) + 1)]; pivot_cols_dynamut2
|
||||
expected_rows_lf = nrow(wf_dynamut2) * (length(wf_dynamut2) - length(pivot_cols_dynamut2))
|
||||
expected_rows_lf
|
||||
|
||||
# LF data: dynamut2
|
||||
lf_dynamut2 = gather(wf_dynamut2
|
||||
# LF data: dynamut2
|
||||
lf_dynamut2 = gather(wf_dynamut2
|
||||
, key = param_type
|
||||
, value = param_value
|
||||
, all_of(dynamut2_dn):tail(static_cols_end,1)
|
||||
, factor_key = TRUE)
|
||||
|
||||
if (nrow(lf_dynamut2) == expected_rows_lf){
|
||||
if (nrow(lf_dynamut2) == expected_rows_lf){
|
||||
cat("\nPASS: long format data created for ", dynamut2_dn)
|
||||
}else{
|
||||
}else{
|
||||
cat("\nFAIL: long format data could not be created for duet")
|
||||
quit()
|
||||
}
|
||||
}
|
||||
|
||||
# NEW columns [outcome and outcome colname]
|
||||
lf_dynamut2$outcome_colname = "ddg_dynamut2_outcome"
|
||||
lf_dynamut2$outcome = lf_dynamut2$ddg_dynamut2_outcome
|
||||
# NEW columns [outcome and outcome colname]
|
||||
lf_dynamut2$outcome_colname = "ddg_dynamut2_outcome"
|
||||
lf_dynamut2$outcome = lf_dynamut2$ddg_dynamut2_outcome
|
||||
|
||||
# DROP static cols
|
||||
lf_dynamut2 = lf_dynamut2[!lf_dynamut2$param_type%in%c(static_cols_end),]
|
||||
lf_dynamut2$param_type = factor(lf_dynamut2$param_type)
|
||||
table(lf_dynamut2$param_type); colnames(lf_dynamut2)
|
||||
# DROP static cols
|
||||
lf_dynamut2 = lf_dynamut2[!lf_dynamut2$param_type%in%c(static_cols_end),]
|
||||
lf_dynamut2$param_type = factor(lf_dynamut2$param_type)
|
||||
table(lf_dynamut2$param_type); colnames(lf_dynamut2)
|
||||
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_dynamut2']] = wf_dynamut2
|
||||
wf_lf_dataL[['lf_dynamut2']] = lf_dynamut2
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_dynamut2']] = wf_dynamut2
|
||||
wf_lf_dataL[['lf_dynamut2']] = lf_dynamut2
|
||||
|
||||
######################################################################################
|
||||
#==================
|
||||
# Consurf: LF
|
||||
#https://consurf.tau.ac.il/overview.php
|
||||
# consurf_score:
|
||||
# <0 (below average): slowly evolving i.e CONSERVED
|
||||
# >0 (above average): rapidly evolving, i.e VARIABLE
|
||||
#table(df$consurf_colour_rev)
|
||||
# TODO
|
||||
#1--> "most_variable", 2--> "", 3-->"", 4-->""
|
||||
#5-->"", 6-->"", 7-->"", 8-->"", 9-->"most_conserved"
|
||||
#====================
|
||||
# WF data: consurf
|
||||
cols_to_select_consurf = c(static_cols_start, c("consurf_outcome", consurf_dn), static_cols_end)
|
||||
wf_consurf = comb_df_sl[, cols_to_select_consurf]
|
||||
######################################################################################
|
||||
#==================
|
||||
# Consurf: LF
|
||||
#https://consurf.tau.ac.il/overview.php
|
||||
# consurf_score:
|
||||
# <0 (below average): slowly evolving i.e CONSERVED
|
||||
# >0 (above average): rapidly evolving, i.e VARIABLE
|
||||
#table(df$consurf_colour_rev)
|
||||
# TODO
|
||||
#1--> "most_variable", 2--> "", 3-->"", 4-->""
|
||||
#5-->"", 6-->"", 7-->"", 8-->"", 9-->"most_conserved"
|
||||
#====================
|
||||
# WF data: consurf
|
||||
cols_to_select_consurf = c(static_cols_start, c("consurf_outcome", consurf_dn), static_cols_end)
|
||||
wf_consurf = comb_df_sl[, cols_to_select_consurf]
|
||||
|
||||
pivot_cols_consurf = cols_to_select_consurf[1: (length(static_cols_start) + 1)]; pivot_cols_consurf
|
||||
expected_rows_lf = nrow(wf_consurf) * (length(wf_consurf) - length(pivot_cols_consurf))
|
||||
expected_rows_lf
|
||||
pivot_cols_consurf = cols_to_select_consurf[1: (length(static_cols_start) + 1)]; pivot_cols_consurf
|
||||
expected_rows_lf = nrow(wf_consurf) * (length(wf_consurf) - length(pivot_cols_consurf))
|
||||
expected_rows_lf
|
||||
|
||||
# when outcome didn't exist
|
||||
#cols_to_select_consurf = c(static_cols_start, c(consurf_dn), static_cols_end)
|
||||
#wf_consurf = comb_df_sl[, cols_to_select_consurf]
|
||||
#
|
||||
# pivot_cols_consurf = cols_to_select_consurf[1: (length(static_cols_start))]; pivot_cols_consurf
|
||||
# expected_rows_lf = nrow(wf_consurf) * (length(wf_consurf) - length(pivot_cols_consurf))
|
||||
# expected_rows_lf
|
||||
# when outcome didn't exist
|
||||
#cols_to_select_consurf = c(static_cols_start, c(consurf_dn), static_cols_end)
|
||||
#wf_consurf = comb_df_sl[, cols_to_select_consurf]
|
||||
#
|
||||
# pivot_cols_consurf = cols_to_select_consurf[1: (length(static_cols_start))]; pivot_cols_consurf
|
||||
# expected_rows_lf = nrow(wf_consurf) * (length(wf_consurf) - length(pivot_cols_consurf))
|
||||
# expected_rows_lf
|
||||
|
||||
# LF data: consurf
|
||||
lf_consurf = gather(wf_consurf
|
||||
# LF data: consurf
|
||||
lf_consurf = gather(wf_consurf
|
||||
, key = param_type
|
||||
, value = param_value
|
||||
, all_of(consurf_dn):tail(static_cols_end,1)
|
||||
, factor_key = TRUE)
|
||||
|
||||
if (nrow(lf_consurf) == expected_rows_lf){
|
||||
if (nrow(lf_consurf) == expected_rows_lf){
|
||||
cat("\nPASS: long format data created for ", consurf_dn)
|
||||
}else{
|
||||
}else{
|
||||
cat("\nFAIL: long format data could not be created for duet")
|
||||
quit()
|
||||
}
|
||||
}
|
||||
|
||||
# NEW columns [outcome and outcome colname]
|
||||
lf_consurf$outcome_colname = "consurf_outcome"
|
||||
lf_consurf$outcome = lf_consurf$consurf_outcome
|
||||
# NEW columns [outcome and outcome colname]
|
||||
lf_consurf$outcome_colname = "consurf_outcome"
|
||||
lf_consurf$outcome = lf_consurf$consurf_outcome
|
||||
|
||||
# DROP static cols
|
||||
lf_consurf = lf_consurf[!lf_consurf$param_type%in%c(static_cols_end),]
|
||||
lf_consurf$param_type = factor(lf_consurf$param_type)
|
||||
table(lf_consurf$param_type); colnames(lf_consurf)
|
||||
# DROP static cols
|
||||
lf_consurf = lf_consurf[!lf_consurf$param_type%in%c(static_cols_end),]
|
||||
lf_consurf$param_type = factor(lf_consurf$param_type)
|
||||
table(lf_consurf$param_type); colnames(lf_consurf)
|
||||
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_consurf']] = wf_consurf
|
||||
wf_lf_dataL[['lf_consurf']] = lf_consurf
|
||||
###########################################################################
|
||||
#==============
|
||||
# SNAP2: LF
|
||||
#==============
|
||||
# WF data: snap2
|
||||
cols_to_select_snap2 = c(static_cols_start, c("snap2_outcome", snap2_dn), static_cols_end)
|
||||
wf_snap2 = comb_df_sl[, cols_to_select_snap2]
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_consurf']] = wf_consurf
|
||||
wf_lf_dataL[['lf_consurf']] = lf_consurf
|
||||
###########################################################################
|
||||
#==============
|
||||
# SNAP2: LF
|
||||
#==============
|
||||
# WF data: snap2
|
||||
cols_to_select_snap2 = c(static_cols_start, c("snap2_outcome", snap2_dn), static_cols_end)
|
||||
wf_snap2 = comb_df_sl[, cols_to_select_snap2]
|
||||
|
||||
pivot_cols_snap2 = cols_to_select_snap2[1: (length(static_cols_start) + 1)]; pivot_cols_snap2
|
||||
expected_rows_lf = nrow(wf_snap2) * (length(wf_snap2) - length(pivot_cols_snap2))
|
||||
expected_rows_lf
|
||||
pivot_cols_snap2 = cols_to_select_snap2[1: (length(static_cols_start) + 1)]; pivot_cols_snap2
|
||||
expected_rows_lf = nrow(wf_snap2) * (length(wf_snap2) - length(pivot_cols_snap2))
|
||||
expected_rows_lf
|
||||
|
||||
# LF data: snap2
|
||||
lf_snap2 = gather(wf_snap2
|
||||
# LF data: snap2
|
||||
lf_snap2 = gather(wf_snap2
|
||||
, key = param_type
|
||||
, value = param_value
|
||||
, all_of(snap2_dn):tail(static_cols_end,1)
|
||||
, factor_key = TRUE)
|
||||
|
||||
if (nrow(lf_snap2) == expected_rows_lf){
|
||||
if (nrow(lf_snap2) == expected_rows_lf){
|
||||
cat("\nPASS: long format data created for ", snap2_dn)
|
||||
}else{
|
||||
}else{
|
||||
cat("\nFAIL: long format data could not be created for duet")
|
||||
quit()
|
||||
}
|
||||
}
|
||||
|
||||
# NEW columns [outcome and outcome colname]
|
||||
lf_snap2$outcome_colname = "snap2_outcome"
|
||||
lf_snap2$outcome = lf_snap2$snap2_outcome
|
||||
# NEW columns [outcome and outcome colname]
|
||||
lf_snap2$outcome_colname = "snap2_outcome"
|
||||
lf_snap2$outcome = lf_snap2$snap2_outcome
|
||||
|
||||
# DROP static cols
|
||||
lf_snap2 = lf_snap2[!lf_snap2$param_type%in%c(static_cols_end),]
|
||||
lf_snap2$param_type = factor(lf_snap2$param_type)
|
||||
table(lf_snap2$param_type); colnames(lf_snap2)
|
||||
# DROP static cols
|
||||
lf_snap2 = lf_snap2[!lf_snap2$param_type%in%c(static_cols_end),]
|
||||
lf_snap2$param_type = factor(lf_snap2$param_type)
|
||||
table(lf_snap2$param_type); colnames(lf_snap2)
|
||||
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_snap2']] = wf_snap2
|
||||
wf_lf_dataL[['lf_snap2']] = lf_snap2
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_snap2']] = wf_snap2
|
||||
wf_lf_dataL[['lf_snap2']] = lf_snap2
|
||||
|
||||
#==============
|
||||
# Provean2: LF
|
||||
#==============
|
||||
# WF data: provean
|
||||
cols_to_select_provean = c(static_cols_start, c("provean_outcome", provean_dn), static_cols_end)
|
||||
wf_provean = comb_df_sl[, cols_to_select_provean]
|
||||
#==============
|
||||
# Provean2: LF
|
||||
#==============
|
||||
# WF data: provean
|
||||
cols_to_select_provean = c(static_cols_start, c("provean_outcome", provean_dn), static_cols_end)
|
||||
wf_provean = comb_df_sl[, cols_to_select_provean]
|
||||
|
||||
pivot_cols_provean = cols_to_select_provean[1: (length(static_cols_start) + 1)]; pivot_cols_provean
|
||||
expected_rows_lf = nrow(wf_provean) * (length(wf_provean) - length(pivot_cols_provean))
|
||||
expected_rows_lf
|
||||
pivot_cols_provean = cols_to_select_provean[1: (length(static_cols_start) + 1)]; pivot_cols_provean
|
||||
expected_rows_lf = nrow(wf_provean) * (length(wf_provean) - length(pivot_cols_provean))
|
||||
expected_rows_lf
|
||||
|
||||
# LF data: provean
|
||||
lf_provean = gather(wf_provean
|
||||
# LF data: provean
|
||||
lf_provean = gather(wf_provean
|
||||
, key = param_type
|
||||
, value = param_value
|
||||
, all_of(provean_dn):tail(static_cols_end,1)
|
||||
, factor_key = TRUE)
|
||||
|
||||
if (nrow(lf_provean) == expected_rows_lf){
|
||||
if (nrow(lf_provean) == expected_rows_lf){
|
||||
cat("\nPASS: long format data created for ", provean_dn)
|
||||
}else{
|
||||
}else{
|
||||
cat("\nFAIL: long format data could not be created for duet")
|
||||
quit()
|
||||
}
|
||||
}
|
||||
|
||||
# NEW columns [outcome and outcome colname]
|
||||
lf_provean$outcome_colname = "provean_outcome"
|
||||
lf_provean$outcome = lf_provean$provean_outcome
|
||||
# NEW columns [outcome and outcome colname]
|
||||
lf_provean$outcome_colname = "provean_outcome"
|
||||
lf_provean$outcome = lf_provean$provean_outcome
|
||||
|
||||
# DROP static cols
|
||||
lf_provean = lf_provean[!lf_provean$param_type%in%c(static_cols_end),]
|
||||
lf_provean$param_type = factor(lf_provean$param_type)
|
||||
table(lf_provean$param_type); colnames(lf_provean)
|
||||
# DROP static cols
|
||||
lf_provean = lf_provean[!lf_provean$param_type%in%c(static_cols_end),]
|
||||
lf_provean$param_type = factor(lf_provean$param_type)
|
||||
table(lf_provean$param_type); colnames(lf_provean)
|
||||
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_provean']] = wf_provean
|
||||
wf_lf_dataL[['lf_provean']] = lf_provean
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_provean']] = wf_provean
|
||||
wf_lf_dataL[['lf_provean']] = lf_provean
|
||||
|
||||
|
||||
###########################################################################
|
||||
# AFFINITY cols
|
||||
###########################################################################
|
||||
#=========================
|
||||
# mCSM-lig:
|
||||
# data filtered by cut off
|
||||
#=========================
|
||||
#---------------------
|
||||
# mCSM-lig: WF and lF
|
||||
#----------------------
|
||||
# WF data: mcsm_lig
|
||||
cols_to_select_mcsm_lig = c(static_cols_start, c("ligand_outcome", mcsm_lig_dn), static_cols_end)
|
||||
wf_mcsm_lig = comb_df_sl_lig[, cols_to_select_mcsm_lig] # filtered df
|
||||
###########################################################################
|
||||
# AFFINITY cols
|
||||
###########################################################################
|
||||
#=========================
|
||||
# mCSM-lig:
|
||||
# data filtered by cut off
|
||||
#=========================
|
||||
#---------------------
|
||||
# mCSM-lig: WF and lF
|
||||
#----------------------
|
||||
# WF data: mcsm_lig
|
||||
cols_to_select_mcsm_lig = c(static_cols_start, c("ligand_outcome", mcsm_lig_dn), static_cols_end)
|
||||
wf_mcsm_lig = comb_df_sl_lig[, cols_to_select_mcsm_lig] # filtered df
|
||||
|
||||
pivot_cols_mcsm_lig = cols_to_select_mcsm_lig[1: (length(static_cols_start) + 1)]; pivot_cols_mcsm_lig
|
||||
expected_rows_lf = nrow(wf_mcsm_lig) * (length(wf_mcsm_lig) - length(pivot_cols_mcsm_lig))
|
||||
expected_rows_lf
|
||||
pivot_cols_mcsm_lig = cols_to_select_mcsm_lig[1: (length(static_cols_start) + 1)]; pivot_cols_mcsm_lig
|
||||
expected_rows_lf = nrow(wf_mcsm_lig) * (length(wf_mcsm_lig) - length(pivot_cols_mcsm_lig))
|
||||
expected_rows_lf
|
||||
|
||||
# LF data: mcsm_lig
|
||||
lf_mcsm_lig = gather(wf_mcsm_lig
|
||||
# LF data: mcsm_lig
|
||||
lf_mcsm_lig = gather(wf_mcsm_lig
|
||||
, key = param_type
|
||||
, value = param_value
|
||||
, all_of(mcsm_lig_dn):tail(static_cols_end,1)
|
||||
, factor_key = TRUE)
|
||||
|
||||
if (nrow(lf_mcsm_lig) == expected_rows_lf){
|
||||
if (nrow(lf_mcsm_lig) == expected_rows_lf){
|
||||
cat("\nPASS: long format data created for ", mcsm_lig_dn)
|
||||
}else{
|
||||
}else{
|
||||
cat("\nFAIL: long format data could not be created for mcsm_lig")
|
||||
quit()
|
||||
}
|
||||
}
|
||||
|
||||
# NEW columns [outcome and outcome colname]
|
||||
lf_mcsm_lig$outcome_colname = "ligand_outcome"
|
||||
lf_mcsm_lig$outcome = lf_mcsm_lig$ligand_outcome
|
||||
# NEW columns [outcome and outcome colname]
|
||||
lf_mcsm_lig$outcome_colname = "ligand_outcome"
|
||||
lf_mcsm_lig$outcome = lf_mcsm_lig$ligand_outcome
|
||||
|
||||
# DROP static cols
|
||||
lf_mcsm_lig = lf_mcsm_lig[!lf_mcsm_lig$param_type%in%c(static_cols_end),]
|
||||
lf_mcsm_lig$param_type = factor(lf_mcsm_lig$param_type)
|
||||
table(lf_mcsm_lig$param_type); colnames(lf_mcsm_lig)
|
||||
# DROP static cols
|
||||
lf_mcsm_lig = lf_mcsm_lig[!lf_mcsm_lig$param_type%in%c(static_cols_end),]
|
||||
lf_mcsm_lig$param_type = factor(lf_mcsm_lig$param_type)
|
||||
table(lf_mcsm_lig$param_type); colnames(lf_mcsm_lig)
|
||||
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_mcsm_lig']] = wf_mcsm_lig
|
||||
wf_lf_dataL[['lf_mcsm_lig']] = lf_mcsm_lig
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_mcsm_lig']] = wf_mcsm_lig
|
||||
wf_lf_dataL[['lf_mcsm_lig']] = lf_mcsm_lig
|
||||
|
||||
#=========================
|
||||
# mmCSM-lig2:
|
||||
# data filtered by cut off
|
||||
#=========================
|
||||
#---------------------
|
||||
# mmCSM-lig2: WF and lF
|
||||
#----------------------
|
||||
# WF data: mmcsm_lig2
|
||||
cols_to_select_mmcsm_lig2 = c(static_cols_start, c("mmcsm_lig_outcome", mmcsm_lig_dn2), static_cols_end)
|
||||
wf_mmcsm_lig2 = comb_df_sl_lig[, cols_to_select_mmcsm_lig2] # filtered df
|
||||
#=========================
|
||||
# mmCSM-lig2:
|
||||
# data filtered by cut off
|
||||
#=========================
|
||||
#---------------------
|
||||
# mmCSM-lig2: WF and lF
|
||||
#----------------------
|
||||
# WF data: mmcsm_lig2
|
||||
cols_to_select_mmcsm_lig2 = c(static_cols_start, c("mmcsm_lig_outcome", mmcsm_lig_dn2), static_cols_end)
|
||||
wf_mmcsm_lig2 = comb_df_sl_lig[, cols_to_select_mmcsm_lig2] # filtered df
|
||||
|
||||
pivot_cols_mmcsm_lig2 = cols_to_select_mmcsm_lig2[1: (length(static_cols_start) + 1)]; pivot_cols_mmcsm_lig2
|
||||
expected_rows_lf = nrow(wf_mmcsm_lig2) * (length(wf_mmcsm_lig2) - length(pivot_cols_mmcsm_lig2))
|
||||
expected_rows_lf
|
||||
pivot_cols_mmcsm_lig2 = cols_to_select_mmcsm_lig2[1: (length(static_cols_start) + 1)]; pivot_cols_mmcsm_lig2
|
||||
expected_rows_lf = nrow(wf_mmcsm_lig2) * (length(wf_mmcsm_lig2) - length(pivot_cols_mmcsm_lig2))
|
||||
expected_rows_lf
|
||||
|
||||
# LF data: mmcsm_lig2
|
||||
lf_mmcsm_lig2 = gather(wf_mmcsm_lig2
|
||||
# LF data: mmcsm_lig2
|
||||
lf_mmcsm_lig2 = gather(wf_mmcsm_lig2
|
||||
, key = param_type
|
||||
, value = param_value
|
||||
, all_of(mmcsm_lig_dn2):tail(static_cols_end,1)
|
||||
, factor_key = TRUE)
|
||||
|
||||
if (nrow(lf_mmcsm_lig2) == expected_rows_lf){
|
||||
if (nrow(lf_mmcsm_lig2) == expected_rows_lf){
|
||||
cat("\nPASS: long format data created for ", mmcsm_lig_dn2)
|
||||
}else{
|
||||
}else{
|
||||
cat("\nFAIL: long format data could not be created for mmcsm_lig2")
|
||||
quit()
|
||||
}
|
||||
}
|
||||
|
||||
# NEW columns [outcome and outcome colname]
|
||||
lf_mmcsm_lig2$outcome_colname = "mmcsm_lig_outcome"
|
||||
lf_mmcsm_lig2$outcome = lf_mmcsm_lig2$mmcsm_lig_outcome
|
||||
# NEW columns [outcome and outcome colname]
|
||||
lf_mmcsm_lig2$outcome_colname = "mmcsm_lig_outcome"
|
||||
lf_mmcsm_lig2$outcome = lf_mmcsm_lig2$mmcsm_lig_outcome
|
||||
|
||||
# DROP static cols
|
||||
lf_mmcsm_lig2 = lf_mmcsm_lig2[!lf_mmcsm_lig2$param_type%in%c(static_cols_end),]
|
||||
lf_mmcsm_lig2$param_type = factor(lf_mmcsm_lig2$param_type)
|
||||
table(lf_mmcsm_lig2$param_type); colnames(lf_mmcsm_lig2)
|
||||
# DROP static cols
|
||||
lf_mmcsm_lig2 = lf_mmcsm_lig2[!lf_mmcsm_lig2$param_type%in%c(static_cols_end),]
|
||||
lf_mmcsm_lig2$param_type = factor(lf_mmcsm_lig2$param_type)
|
||||
table(lf_mmcsm_lig2$param_type); colnames(lf_mmcsm_lig2)
|
||||
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_mmcsm_lig2']] = wf_mmcsm_lig2
|
||||
wf_lf_dataL[['lf_mmcsm_lig2']] = lf_mmcsm_lig2
|
||||
# Assign them to the output list
|
||||
wf_lf_dataL[['wf_mmcsm_lig2']] = wf_mmcsm_lig2
|
||||
wf_lf_dataL[['lf_mmcsm_lig2']] = lf_mmcsm_lig2
|
||||
|
||||
#=========================
|
||||
# mcsm-ppi2 affinity
|
||||
# data filtered by cut off
|
||||
#========================
|
||||
if (tolower(gene)%in%geneL_ppi2){
|
||||
#=========================
|
||||
# mcsm-ppi2 affinity
|
||||
# data filtered by cut off
|
||||
#========================
|
||||
if (tolower(gene)%in%geneL_ppi2){
|
||||
#-----------------
|
||||
# mCSM-PPI2: WF and lF
|
||||
#-----------------
|
||||
|
|
@ -724,15 +773,15 @@ if (tolower(gene)%in%geneL_ppi2){
|
|||
wf_lf_dataL[['wf_mcsm_ppi2']] = wf_mcsm_ppi2
|
||||
wf_lf_dataL[['lf_mcsm_ppi2']] = lf_mcsm_ppi2
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
#====================
|
||||
# mcsm-NA affinity
|
||||
# data filtered by cut off
|
||||
#====================
|
||||
if (tolower(gene)%in%geneL_na){
|
||||
#====================
|
||||
# mcsm-NA affinity
|
||||
# data filtered by cut off
|
||||
#====================
|
||||
if (tolower(gene)%in%geneL_na){
|
||||
#---------------
|
||||
# mCSM-NA: WF and lF
|
||||
#-----------------
|
||||
|
|
@ -772,8 +821,8 @@ if (tolower(gene)%in%geneL_na){
|
|||
wf_lf_dataL[['wf_mcsm_na']] = wf_mcsm_na
|
||||
wf_lf_dataL[['lf_mcsm_na']] = lf_mcsm_na
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
return(wf_lf_dataL)
|
||||
return(wf_lf_dataL)
|
||||
}
|
||||
############################################################################
|
||||
|
|
|
|||
|
|
@ -12,20 +12,19 @@ geneL_na = c("gid", "rpob")
|
|||
geneL_ppi2 = c("alr", "embb", "katg", "rpob")
|
||||
|
||||
if (tolower(gene)%in%geneL_na){
|
||||
|
||||
infilename_nca = paste0("/home/tanu/git/Misc/mcsm_na_dist/"
|
||||
, tolower(gene), "_nca_distances.csv")
|
||||
}
|
||||
#========================================================
|
||||
# plotting_data(): formatting data for plots
|
||||
# input args:
|
||||
## input csv file
|
||||
## lig cut off dist, default = 10 Ang
|
||||
## input csv file
|
||||
## lig cut off dist, default = 10 Ang
|
||||
# output: list of 4 dfs, that need to be decompressed
|
||||
## my_df
|
||||
## my_df_u
|
||||
## my_df_u_lig
|
||||
## dup_muts
|
||||
## my_df
|
||||
## my_df_u
|
||||
## my_df_u_lig
|
||||
## dup_muts
|
||||
#========================================================
|
||||
#lig_dist_colname = 'ligand_distance' or global var LigDist_colname
|
||||
#lig_dist_cutoff = 10 or global var LigDist_cutoff
|
||||
|
|
@ -34,24 +33,24 @@ plotting_data <- function(df
|
|||
, gene # ADDED
|
||||
, lig_dist_colname
|
||||
, lig_dist_cutoff) {
|
||||
my_df = data.frame()
|
||||
my_df_u = data.frame()
|
||||
my_df_u_lig = data.frame()
|
||||
dup_muts = data.frame()
|
||||
my_df = data.frame()
|
||||
my_df_u = data.frame()
|
||||
my_df_u_lig = data.frame()
|
||||
dup_muts = data.frame()
|
||||
|
||||
#===========================
|
||||
# Read file: struct params
|
||||
#===========================
|
||||
#df = read.csv(infile_params, header = T)
|
||||
#===========================
|
||||
# Read file: struct params
|
||||
#===========================
|
||||
#df = read.csv(infile_params, header = T)
|
||||
|
||||
cat("\nInput dimensions:", dim(df))
|
||||
cat("\nInput dimensions:", dim(df))
|
||||
|
||||
#==================================
|
||||
# extract unique mutation entries
|
||||
#==================================
|
||||
#==================================
|
||||
# extract unique mutation entries
|
||||
#==================================
|
||||
|
||||
# check for duplicate mutations
|
||||
if ( length(unique(df$mutationinformation)) != length(df$mutationinformation)){
|
||||
# check for duplicate mutations
|
||||
if ( length(unique(df$mutationinformation)) != length(df$mutationinformation)){
|
||||
cat(paste0("\nCAUTION:", " Duplicate mutations identified"
|
||||
, "\nExtracting these...\n"))
|
||||
#cat(my_df[duplicated(my_df$mutationinformation),])
|
||||
|
|
@ -61,53 +60,94 @@ if ( length(unique(df$mutationinformation)) != length(df$mutationinformation)){
|
|||
, "\nNo. of unique duplicate mutations:", dup_muts_nu
|
||||
, "\n\nExtracting df with unique mutations only\n"))
|
||||
my_df_u = df[!duplicated(df$mutationinformation),]
|
||||
}else{
|
||||
} else {
|
||||
cat(paste0("\nNo duplicate mutations detected\n"))
|
||||
my_df_u = df
|
||||
}
|
||||
}
|
||||
|
||||
upos = unique(my_df_u$position)
|
||||
cat("\nDim of clean df:"); cat(dim(my_df_u), "\n")
|
||||
cat("\nNo. of unique mutational positions:"); cat(length(upos), "\n")
|
||||
#===============================================
|
||||
# ADD : na distance column for genes with nucleic acid affinity
|
||||
#===============================================
|
||||
#gid_na_distcol
|
||||
if (tolower(gene)%in%geneL_na){
|
||||
upos = unique(my_df_u$position)
|
||||
cat("\nDim of clean df:"); cat(dim(my_df_u), "\n")
|
||||
cat("\nNo. of unique mutational positions:"); cat(length(upos), "\n")
|
||||
#===============================================
|
||||
# ADD : na distance column for genes with nucleic acid affinity
|
||||
#===============================================
|
||||
# if (tolower(gene)%in%geneL_na){
|
||||
#
|
||||
# distcol_nca_name = read.csv(infilename_nca, header = F)
|
||||
# head(distcol_nca_name)
|
||||
# colnames(distcol_nca_name) <- c("mutationinformation", "nca_distance")
|
||||
# head(distcol_nca_name)
|
||||
# class(distcol_nca_name)
|
||||
#
|
||||
# mcol = colnames(distcol_nca_name)[colnames(distcol_nca_name)%in%colnames(my_df_u)]
|
||||
# mcol
|
||||
# head(my_df_u$mutationinformation)
|
||||
# head(distcol_nca_name$mutationinformation)
|
||||
#
|
||||
# my_df_u = merge(my_df_u, distcol_nca_name,
|
||||
# by = "mutationinformation",
|
||||
# all = T)
|
||||
#
|
||||
# }
|
||||
|
||||
if (tolower(gene)%in%geneL_na){
|
||||
distcol_nca_name = read.csv(infilename_nca, header = F)
|
||||
|
||||
if (tolower(gene)=='rpob'){
|
||||
print('WARNING: running special-case handler for rpoB')
|
||||
|
||||
# create 5uhc equivalent column for mutationinformation
|
||||
my_df_u$X5uhc_mutationinformation = paste0(my_df_u$wild_type,
|
||||
my_df_u$X5uhc_position,
|
||||
my_df_u$mutant_type)
|
||||
|
||||
colnames(distcol_nca_name) <- c("X5uhc_mutationinformation", "nca_distance")
|
||||
|
||||
# do stuff here
|
||||
mcol = colnames(distcol_nca_name)[colnames(distcol_nca_name)%in%colnames(my_df_u)]
|
||||
cat(paste0("\nMerging for gene: ", tolower(gene), "\non column: ", mcol))
|
||||
|
||||
head(my_df_u$mutationinformation)
|
||||
head(distcol_nca_name$X5uhc_mutationinformation)
|
||||
|
||||
my_df_u = merge(my_df_u, distcol_nca_name,
|
||||
by = "X5uhc_mutationinformation",
|
||||
all = T)
|
||||
|
||||
} else {
|
||||
head(distcol_nca_name)
|
||||
colnames(distcol_nca_name) <- c("mutationinformation", "nca_distance")
|
||||
head(distcol_nca_name)
|
||||
class(distcol_nca_name)
|
||||
|
||||
mcol = colnames(distcol_nca_name)[colnames(distcol_nca_name)%in%colnames(my_df_u)]
|
||||
mcol
|
||||
cat(paste0("\nMerging for gene: ", tolower(gene), "\non column: ", mcol))
|
||||
head(my_df_u$mutationinformation)
|
||||
head(distcol_nca_name$mutationinformation)
|
||||
|
||||
my_df_u = merge(my_df_u, distcol_nca_name,
|
||||
by = "mutationinformation",
|
||||
all = T)
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
#===============================================
|
||||
# extract mutations <10 Angstroms and symbol
|
||||
#===============================================
|
||||
table(my_df_u[[lig_dist_colname]] < lig_dist_cutoff)
|
||||
#===============================================
|
||||
# extract mutations <10 Angstroms and symbol
|
||||
#===============================================
|
||||
table(my_df_u[[lig_dist_colname]] < lig_dist_cutoff)
|
||||
|
||||
my_df_u_lig = my_df_u[my_df_u[[lig_dist_colname]] < lig_dist_cutoff,]
|
||||
my_df_u_lig = my_df_u[my_df_u[[lig_dist_colname]] < lig_dist_cutoff,]
|
||||
|
||||
cat(paste0("There are ", nrow(my_df_u_lig), " sites lying within 10\u212b of the ligand\n"))
|
||||
cat(paste0("There are ", nrow(my_df_u_lig), " sites lying within 10\u212b of the ligand\n"))
|
||||
|
||||
# return list of DFs
|
||||
my_df = df
|
||||
#df_names = c("my_df", "my_df_u", "my_df_u_lig", "dup_muts")
|
||||
all_df = list(my_df, my_df_u, my_df_u_lig, dup_muts)
|
||||
#all_df = Map(setNames, all_df, df_names)
|
||||
# return list of DFs
|
||||
my_df = df
|
||||
#df_names = c("my_df", "my_df_u", "my_df_u_lig", "dup_muts")
|
||||
all_df = list(my_df, my_df_u, my_df_u_lig, dup_muts)
|
||||
#all_df = Map(setNames, all_df, df_names)
|
||||
|
||||
return(all_df)
|
||||
return(all_df)
|
||||
}
|
||||
########################################################################
|
||||
# end of data extraction and cleaning for plots #
|
||||
########################################################################
|
||||
|
||||
|
|
|
|||
|
|
@ -60,8 +60,8 @@ pd_df = plotting_data(mcsm_df
|
|||
my_df = pd_df[[1]]
|
||||
my_df_u = pd_df[[2]] # this forms one of the input for combining_dfs_plotting()
|
||||
|
||||
max_ang <- round(max(my_df_u[LigDist_colname]))
|
||||
min_ang <- round(min(my_df_u[LigDist_colname]))
|
||||
max_ang <- round(max(my_df_u[[LigDist_colname]]))
|
||||
min_ang <- round(min(my_df_u[[LigDist_colname]]))
|
||||
|
||||
cat("\nLigand distance colname:", LigDist_colname
|
||||
, "\nThe max distance", gene, "structure df" , ":", max_ang, "\u212b"
|
||||
|
|
@ -128,6 +128,11 @@ geneL_normal = c("pnca")
|
|||
geneL_na = c("gid", "rpob")
|
||||
geneL_ppi2 = c("alr", "embb", "katg", "rpob")
|
||||
|
||||
# geneL_normal = c("pnca")
|
||||
# geneL_both = c("rpob")
|
||||
# geneL_ppi2 = c("alr", "embb", "katg")
|
||||
# geneL_na = c("gid")
|
||||
|
||||
all_dm_om_df = dm_om_wf_lf_data(df = merged_df3, gene = gene)
|
||||
|
||||
wf_duet = all_dm_om_df[['wf_duet']]
|
||||
|
|
@ -158,15 +163,27 @@ lf_provean = all_dm_om_df[['lf_provean']]
|
|||
wf_dist_gen = all_dm_om_df[['wf_dist_gen']]
|
||||
lf_dist_gen = all_dm_om_df[['lf_dist_gen']]
|
||||
|
||||
# ppi2 genes
|
||||
if (tolower(gene)%in%geneL_ppi2){
|
||||
wf_mcsm_ppi2 = all_dm_om_df[['wf_mcsm_ppi2']]
|
||||
lf_mcsm_ppi2 = all_dm_om_df[['lf_mcsm_ppi2']]
|
||||
}
|
||||
|
||||
# na genes
|
||||
if (tolower(gene)%in%geneL_na){
|
||||
wf_mcsm_na = all_dm_om_df[['wf_mcsm_na']]
|
||||
lf_mcsm_na = all_dm_om_df[['lf_mcsm_na']]
|
||||
}
|
||||
|
||||
if (tolower(gene)%in%geneL_ppi2){
|
||||
wf_mcsm_ppi2 = all_dm_om_df[['wf_mcsm_ppi2']]
|
||||
lf_mcsm_ppi2 = all_dm_om_df[['lf_mcsm_ppi2']]
|
||||
}
|
||||
# both ppi2+na genes:: NOT NEEDED Here as its is handled by the two ifs above
|
||||
# if (tolower(gene)%in%geneL_both){
|
||||
# wf_mcsm_ppi2 = all_dm_om_df[['wf_mcsm_ppi2']]
|
||||
# lf_mcsm_ppi2 = all_dm_om_df[['lf_mcsm_ppi2']]
|
||||
#
|
||||
# wf_mcsm_na = all_dm_om_df[['wf_mcsm_na']]
|
||||
# lf_mcsm_na = all_dm_om_df[['lf_mcsm_na']]
|
||||
# }
|
||||
|
||||
|
||||
s2 = c("\nSuccessfully sourced other_plots_data.R")
|
||||
cat(s2)
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue