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