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added logo_multiple_muts.R

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Tanushree Tunstall 2020-09-11 18:12:06 +01:00
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scripts/plotting/logo_multiple_muts.R Normal file
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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