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