diff --git a/scripts/plotting/logo_multiple_muts.R b/scripts/plotting/logo_multiple_muts.R
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+++ b/scripts/plotting/logo_multiple_muts.R
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+getwd()
+#setwd("~/Documents/git/LSHTM_Y1_PNCA/combined_v3/logo_plot") # wor_mychisqk
+setwd("~/git/LSHTM_Y1_PNCA/combined_v3/logo_plot") # thinkpad
+#setwd("/Users/tanu/git/LSHTM_Y1_PNCA/combined_v3/logo_plot") # mac
+getwd()
+
+#########################################################
+# 1: Installing and loading required packages
+#########################################################
+
+source("../../Header_TT.R")
+
+#source("barplot_colour_function.R")
+
+#install.packages("ggseqlogo")
+
+library(ggseqlogo)
+
+
+########################################################################
+#               end of loading libraries and functions                 #
+########################################################################
+setwd("/home/tanu/git/LSHTM_analysis/plotting_test")
+
+source("../scripts/plotting/combining_dfs_plotting.R")
+
+# since we will be using df without NA, its best to delete the ones with NA
+rm(merged_df2, merged_df3)
+
+
+###########################
+# 3: Data for_mychisq DUET plots
+# you need merged_df3_comp 
+# since these have unique SNPs
+###########################
+
+#<<<<<<<<<<<<<<<<<<<<<<<<<
+# REASSIGNMENT
+my_df  = merged_df3_comp 
+my_df = merged_df3 #try!
+#<<<<<<<<<<<<<<<<<<<<<<<<<
+
+colnames(my_df)
+str(my_df)
+
+rownames(my_df) = my_df$Mutationinfor_mychisqmation
+
+c1 = unique(my_df$position) #96
+nrow(my_df) #189
+
+#get freq count of positions so you can subset freq<1
+require(data.table)
+setDT(my_df)[, occurrence := .N, by = .(position)] #189, 36
+
+table(my_df$position); table(my_df$occurrence)
+
+#extract freq_pos>1
+my_data_snp = my_df[my_df$occurrence!=1,] #144, 36
+u = unique(my_data_snp$position) #51
+
+########################################################################
+#               end of data extraction and cleaning for_mychisq plots          #
+########################################################################
+
+
+
+
+#########################################################
+#Task: To generate a logo plot  or_mychisq bar plot but coloured 
+#aa properties.
+#step1: read mcsm file and or_mychisq file
+#step2: plot wild type positions
+#step3: plot mutants per position coloured by aa properties
+#step4: make the size of the letters/bars prop to or_mychisq if you can!
+#########################################################
+##useful links
+#https://stackoverflow.com/questions/5438474/plotting-a-sequence-logo-using-ggplot2
+#https://omarwagih.github.io/ggseqlogo/
+#https://kkdey.github.io/Logolas-pages/wor_mychisqkflow.html
+#A new sequence logo plot to highlight enrichment and depletion.
+#    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6288878/
+
+
+##very good: http://www.cbs.dtu.dk/biotools/Seq2Logo-2.0/
+
+
+
+#############
+#PLOTS: Bar plot with aa properties
+#using gglogo
+#useful links: https://stackoverflow.com/questions/5438474/plotting-a-sequence-logo-using-ggplot2
+#############
+#following example
+require(ggplot2)
+require(reshape2)
+library(gglogo)
+library(ggrepel)
+#lmf <- melt(logodf, id.var='pos')
+foo = my_data_snp[, c("position", "mutant_type","duet_scaled", "or_mychisq", "mut_prop_polarity", "mut_prop_water") ]
+#144, 6
+head(foo)
+
+foo = foo[or_mychisqder(foo$position),]
+head(foo)
+
+#==============
+# matrix for_mychisq mutant type
+# frequency of mutant type by position
+#==============
+table(my_data_snp$mutant_type, my_data_snp$position)
+tab = table(my_data_snp$mutant_type, my_data_snp$position)
+class(tab)
+# unclass to convert to matrix
+tab = unclass(tab)
+tab = as.matrix(tab, rownames = T)
+#should be TRUE
+is.matrix(tab)
+
+rownames(tab) #aa
+colnames(tab) #pos
+
+#**************
+# Plot 1: mutant logo
+#**************
+# generate seq logo
+p0 = ggseqlogo(tab
+               , method = 'custom'
+               , seq_type = 'aa'
+               #, col_scheme = "taylor_mychisq"
+               #, col_scheme = "chemistry2"
+               ) + 
+  #ylab('my custom height') +
+  theme(axis.text.x = element_blank()) +
+  theme_logo()+ 
+ # scale_x_continuous(breaks=1:51, parse (text = colnames(tab)) )
+  scale_x_continuous(breaks = 1:ncol(tab)
+                   , labels = colnames(tab))+
+  scale_y_continuous( breaks = 1:5
+                      , limits = c(0, 6))
+
+p0
+
+# further customisation
+
+p1 = p0 + theme(legend.position = "bottom"
+                , legend.title = element_blank()
+                , legend.text = element_text(size = 20)
+                , axis.text.x = element_text(size = 20, angle = 90)
+                , axis.text.y = element_text(size = 20, angle = 90))
+p1
+
+#==============
+# matrix for_mychisq wild type
+# frequency of wild type by position
+#==============  
+tab_wt = table(my_data_snp$wild_type, my_data_snp$position); tab_wt #17, 51
+tab_wt = unclass(tab_wt)
+
+#remove wt duplicates
+wt = my_data_snp[, c("position", "wild_type")] #144, 2
+wt = wt[!duplicated(wt),]#51, 2
+
+tab_wt = table(wt$wild_type, wt$position); tab_wt # should all be 1
+rownames(tab_wt)
+rownames(tab)
+
+#**************
+# Plot 2: for_mychisq wild_type
+# with custom x axis to reflect my aa positions
+#**************
+# sanity check: MUST BE TRUE
+# for_mychisq the cor_mychisqrectnes of the x axis
+identical(colnames(tab), colnames(tab_wt))
+identical(ncol(tab), ncol(tab_wt))
+
+p2 = ggseqlogo(tab_wt
+               , method = 'custom'
+               , seq_type = 'aa'
+               #, col_scheme = "taylor"
+               #, col_scheme = chemistry2
+               ) + 
+  #ylab('my custom height') +
+  theme(axis.text.x = element_blank()
+        , axis.text.y = element_blank()) +
+  theme_logo() +
+    scale_x_continuous(breaks = 1:ncol(tab_wt)
+                       , labels = colnames(tab_wt)) +
+    scale_y_continuous( limits = c(0, 5))
+p2
+# further customise
+
+p3 = p2 +
+  theme(legend.position = "none"
+        , axis.text.x = element_text(size = 20
+                                   , angle = 90)
+        , axis.text.y = element_blank()) 
+
+p3
+
+
+# Now combine using cowplot, which ensures the plots are aligned
+suppressMessages( require(cowplot) )
+
+plot_grid(p1, p3, ncol = 1, align = 'v') #+ 
+ # background_grid(minor_mychisq = "xy"
+#                  , size.minor_mychisq = 1
+#                  , colour.minor_mychisq = "grey86")
+
+
+#colour scheme
+#https://rdrr.io/cran/ggseqlogo/src/R/col_schemes.r
+