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