playing with MSA plots to allow filtering of positions, arghhh

scripts/plotting/redundant/logo_data.R

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+#!/usr/bin/env Rscript  
+#########################################################
+# TASK: Script to format data for Logo_plots
+#########################################################
+#-------------------------
+# choose df for logoplot
+#-------------------------
+logo_data = merged_df3
+#logo_data = merged_df3_comp
+#logo_data = merged_df2 # can't be used because of multiple snps
+
+# quick checks
+colnames(logo_data)
+str(logo_data)
+
+c1 = unique(logo_data$position) 
+nrow(logo_data)
+cat("No. of rows in my_data:", nrow(logo_data)
+    , "\nDistinct positions corresponding to snps:", length(c1)
+    , "\n===========================================================")
+#=======================================================================
+#==================
+# logo data: OR
+#==================
+foo = logo_data[, c("position"
+                    , "mutant_type","duet_scaled", "or_mychisq"
+                    , "mut_prop_polarity", "mut_prop_water")] 
+
+logo_data$log10or = log10(logo_data$or_mychisq)
+logo_data_plot = logo_data[, c("position"
+                               , "mutant_type", "or_mychisq", "log10or")]
+
+logo_data_plot_or = logo_data[, c("position", "mutant_type", "or_mychisq")]
+wide_df_or  =  logo_data_plot_or %>% spread(position, or_mychisq, fill = 0.0)
+
+wide_df_or = as.matrix(wide_df_or)
+rownames(wide_df_or) = wide_df_or[,1]
+dim(wide_df_or)
+wide_df_or = wide_df_or[,-1]
+str(wide_df_or)
+
+position_or = as.numeric(colnames(wide_df_or))
+
+#==================
+# logo data: logOR
+#==================
+logo_data_plot_logor = logo_data[, c("position", "mutant_type", "log10or")]
+wide_df_logor <- logo_data_plot_logor %>% spread(position, log10or, fill = 0.0)
+
+wide_df_logor = as.matrix(wide_df_logor)
+
+rownames(wide_df_logor) = wide_df_logor[,1]
+wide_df_logor = subset(wide_df_logor, select = -c(1) )
+colnames(wide_df_logor)
+wide_df_logor_m = data.matrix(wide_df_logor)
+
+rownames(wide_df_logor_m)
+colnames(wide_df_logor_m)
+
+position_logor = as.numeric(colnames(wide_df_logor_m))
+
+#===============================
+# logo data: multiple nsSNPs (>1)
+#=================================
+#require(data.table)
+
+# get freq count of positions so you can subset freq<1
+setDT(logo_data)[, mut_pos_occurrence := .N, by = .(position)] 
+
+table(logo_data$position)
+table(logo_data$mut_pos_occurrence)
+
+max_mut = max(table(logo_data$position))
+
+# extract freq_pos > 1
+my_data_snp = logo_data[logo_data$mut_pos_occurrence!=1,] 
+u = unique(my_data_snp$position)
+max_mult_mut = max(table(my_data_snp$position))
+
+if (nrow(my_data_snp) == nrow(logo_data) - table(logo_data$mut_pos_occurrence)[[1]] ){
+  
+  cat("PASS: positions with  multiple muts extracted"
+      , "\nNo. of mutations:", nrow(my_data_snp)
+      , "\nNo. of positions:", length(u)
+      , "\nMax no. of muts at any position", max_mult_mut)
+}else{
+  cat("FAIL: positions with multiple muts could NOT be extracted"
+      , "\nExpected:",nrow(logo_data) - table(logo_data$mut_pos_occurrence)[[1]]
+      , "\nGot:", nrow(my_data_snp) )
+}
+
+cat("\nNo. of sites with only 1 mutations:", table(logo_data$mut_pos_occurrence)[[1]])
+
+#--------------------------------------
+# matrix for_mychisq mutant type
+# frequency of mutant type by position
+#---------------------------------------
+table(my_data_snp$mutant_type, my_data_snp$position)
+tab_mt = table(my_data_snp$mutant_type, my_data_snp$position)
+class(tab_mt)
+
+# unclass to convert to matrix
+tab_mt = unclass(tab_mt)
+tab_mt = as.matrix(tab_mt, rownames = T)
+
+# should be TRUE
+is.matrix(tab_mt)
+
+rownames(tab_mt) #aa
+colnames(tab_mt) #pos
+
+#-------------------------------------
+# matrix for wild type
+# frequency of wild type by position
+#-------------------------------------
+tab_wt = table(my_data_snp$wild_type, my_data_snp$position); tab_wt
+tab_wt = unclass(tab_wt)
+
+# remove wt duplicates
+wt = my_data_snp[, c("position", "wild_type")]
+wt = wt[!duplicated(wt),]
+
+tab_wt = table(wt$wild_type, wt$position); tab_wt # should all be 1
+
+rownames(tab_wt)
+rownames(tab_wt)
+
+identical(colnames(tab_mt), colnames(tab_wt))
+identical(ncol(tab_mt), ncol(tab_wt))
+
+#----------------------------------
+# logo data OR: multiple nsSNPs (>1)
+#----------------------------------
+logo_data_or_mult = my_data_snp[, c("position", "mutant_type", "or_mychisq")]
+#wide_df_or  =  logo_data_or %>% spread(position, or_mychisq, fill = 0.0)
+wide_df_or_mult  =  logo_data_or_mult %>% spread(position, or_mychisq, fill = NA)
+
+wide_df_or_mult = as.matrix(wide_df_or_mult)
+rownames(wide_df_or_mult) = wide_df_or_mult[,1]
+wide_df_or_mult = wide_df_or_mult[,-1]
+str(wide_df_or_mult)
+
+position_or_mult = as.numeric(colnames(wide_df_or_mult))
+