208 lines
5.4 KiB
R
208 lines
5.4 KiB
R
getwd()
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setwd("~/git/LSHTM_analysis/mcsm_analysis/pyrazinamide/scripts/plotting")
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getwd()
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############################################################
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# 1: Installing and loading required packages and functions
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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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#library(tidyverse)
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###########################
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#2: Read file: normalised file, output of step 4 mcsm pipeline
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###########################
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#my_df <- read.csv("../../Data/mcsm_complex1_normalised.csv"
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# , row.names = 1
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# , stringsAsFactors = F
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# , header = T)
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# call script combining_df
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source("../combining_two_df_lig.R")
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#---------------------- PAY ATTENTION
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# the above changes the working dir
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# from Plotting to Scripts"
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#---------------------- PAY ATTENTION
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#==========================
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# This will return:
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# df with NA for pyrazinamide:
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#merged_df2
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#merged_df2_comp
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# df without NA for pyrazinamide:
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#merged_df3
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#merged_df3_comp
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#==========================
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###########################
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# Data to choose:
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# We will be using the small dfs
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# to generate the coloured axis
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###########################
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# uncomment as necessary
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#!!!!!!!!!!!!!!!!!!!!!!!
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# REASSIGNMENT
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my_df = merged_df3
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#my_df = merged_df3_comp
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#!!!!!!!!!!!!!!!!!!!!!!!
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# delete variables not required
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rm(merged_df2, merged_df2_comp, merged_df3, merged_df3_comp)
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str(my_df)
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my_df$Position
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c1 = my_df[my_df$Mutationinformation == "A134V",]
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# order my_df by Position
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my_df_o = my_df[order(my_df$Position),]
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head(my_df_o$Position); tail(my_df_o$Position)
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c2 = my_df_o[my_df_o$Mutationinformation == "A134V",]
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# sanity check
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if (sum(table(c1 == c2)) == ncol(my_df)){
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print ("Sanity check passsd")
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}else{
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print ("Error!: Please debug your code")
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}
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rm(my_df, c1, c2)
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# create a new df with unique position numbers and cols
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Position = unique(my_df_o$Position)
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Position_cols = as.data.frame(Position)
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head(Position_cols) ; tail(Position_cols)
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# specify active site residues and bg colour
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Position = c(49, 51, 57, 71
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, 8, 96, 138
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, 13, 68
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, 103, 137
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, 133, 134) #13
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lab_bg = rep(c("purple"
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, "yellow"
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, "cornflowerblue"
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, "blue"
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, "green"), times = c(4, 3, 2, 2, 2)
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)
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# second bg colour for active site residues
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#lab_bg2 = rep(c("white"
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# , "green" , "white", "green"
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# , "white"
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# , "white"
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# , "white"), times = c(4
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# , 1, 1, 1
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# , 2
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# , 2
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# , 2)
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#)
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#%%%%%%%%%
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# revised: leave the second box coloured as the first one incase there is no second colour
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#%%%%%%%%%
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lab_bg2 = rep(c("purple"
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, "green", "yellow", "green"
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, "cornflowerblue"
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, "blue"
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, "green"), times = c(4
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, 1, 1, 1
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, 2
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, 2
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, 2))
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# fg colour for labels for active site residues
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lab_fg = rep(c("white"
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, "black"
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, "black"
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, "white"
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, "black"), times = c(4, 3, 2, 2, 2))
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#%%%%%%%%%
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# revised: make the purple ones black
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# fg colour for labels for active site residues
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#%%%%%%%%%
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#lab_fg = rep(c("black"
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# , "black"
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# , "black"
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# , "white"
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# , "black"), times = c(4, 3, 2, 2, 2))
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# combined df with active sites, bg and fg colours
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aa_cols_ref = data.frame(Position
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, lab_bg
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, lab_bg2
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, lab_fg
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, stringsAsFactors = F) #13, 4
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str(Position_cols); class(Position_cols)
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str(aa_cols_ref); class(aa_cols_ref)
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# since Position is int and numeric in the two dfs resp,
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# converting numeric to int for consistency
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aa_cols_ref$Position = as.integer(aa_cols_ref$Position)
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class(aa_cols_ref$Position)
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#===========
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# Merge 1: merging Positions df (Position_cols) and
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# active site cols (aa_cols_ref)
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# linking column: "Position"
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# This is so you can have colours defined for all 130 positions
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#===========
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head(Position_cols$Position); head(aa_cols_ref$Position)
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mut_pos_cols = merge(Position_cols, aa_cols_ref
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, by = "Position"
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, all.x = TRUE)
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head(mut_pos_cols)
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# replace NA's
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# :column "lab_bg" with "white"
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# : column "lab_fg" with "black"
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mut_pos_cols$lab_bg[is.na(mut_pos_cols$lab_bg)] <- "white"
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mut_pos_cols$lab_bg2[is.na(mut_pos_cols$lab_bg2)] <- "white"
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mut_pos_cols$lab_fg[is.na(mut_pos_cols$lab_fg)] <- "black"
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head(mut_pos_cols)
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#===========
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# Merge 2: Merge mut_pos_cols with mcsm df
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# Now combined the 130 positions with aa colours with
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# the mcsm_data
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#===========
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# dfs to merge
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df0 = my_df_o
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df1 = mut_pos_cols
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# check the column on which merge will be performed
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head(df0$Position); tail(df0$Position)
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head(df1$Position); tail(df1$Position)
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# should now have 3 extra columns
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my_df = merge(df0, df1
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, by = "Position"
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, all.x = TRUE)
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# sanity check
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my_df[my_df$Position == "49",]
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my_df[my_df$Position == "13",]
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my_df$Position
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# clear variables
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rm(aa_cols_ref
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, df0
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, df1
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, my_df_o
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, Position_cols
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, lab_bg
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, lab_bg2
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, lab_fg
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, Position
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)
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