renamed dist_plots.R to dist_plots_check.R as its exploratory
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scripts/plotting/dist_plots_check.R
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291
scripts/plotting/dist_plots_check.R
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#!/usr/bin/env Rscript
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#########################################################
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# TASK: producing boxplots for dr and other muts
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#########################################################
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#=======================================================================
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# working dir and loading libraries
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getwd()
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setwd("~/git/LSHTM_analysis/scripts/plotting")
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getwd()
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#source("Header_TT.R")
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library(tidyverse)
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library(ggplot2)
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library(data.table)
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library(dplyr)
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#=========
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# Input
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#=========
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#source("combining_dfs_plotting.R")
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source("output_tables.R")
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#grid(nx=NA,ny=NULL,lty=1,lwd=1,col="gray")
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##########################################################
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#====================
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# OR distributions
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#====================
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par(mfrow=c(2,2))
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#-----------
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# or_mychisq: raw
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#-----------
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ylim_or = max(density(merged_df3$or_mychisq, na.rm = T)$y)
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ylim_or
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hist(merged_df3$or_mychisq
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, prob = TRUE
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, col = "grey"
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, border= "black"
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, ylim = c(0, ylim_or)
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, xlab = "Odds Ratio"
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, main = "Odds Ratio")
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box(bty="l")
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lines(density(merged_df3$or_mychisq, na.rm = T, bw = "nrd0") # default
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, col = "black"
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, lwd = 2)
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#plot(density(merged_df3$or_mychisq, na.rm = T, bw = "nrd0"))
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#-----------
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# or_mychisq: log10
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#-----------
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ylim_or_log = max(density(log10(merged_df3$or_mychisq), na.rm = T)$y)
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hist(log10(merged_df3$or_mychisq)
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, prob = TRUE
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, col = "grey"
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, border= "black"
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, ylim = c(0, ylim_or_log)
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, xlab = "Log10 (Odds Ratio)"
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, main = "Odds Ratio")
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box(bty="l")
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lines(density(log10(merged_df3$or_mychisq), na.rm = T, bw = "nrd0") # default
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, col = "black"
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, lwd = 2)
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#======================================================================
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#-------------------
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# adjusted OR: raw
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#-------------------
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ylim_or_ad = max(density(merged_df3$or_kin, na.rm = T)$y)
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ylim_or_ad
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hist(merged_df3$or_kin
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, prob = TRUE
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, col = "grey"
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, border= "black"
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, ylim = c(0, ylim_or_ad)
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, xlab = "Adjusted Odds Ratio"
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, main = "Adjusted Odds Ratio")
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box(bty="l")
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lines(density(merged_df3$or_kin, na.rm = T, bw = "nrd0") # default
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, col = "black"
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, lwd = 2)
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#plot(density(merged_df3$or_kin, na.rm = T, bw = "nrd0"))
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#--------------------
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# adjusted OR: log10
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#---------------------
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ylim_or_ad_log = max(density(log10(merged_df3$or_kin), na.rm = T)$y)
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hist(log10(merged_df3$or_kin)
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, prob = TRUE
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, col = "grey"
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, border= "black"
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, ylim = c(0, ylim_or_ad_log)
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, xlab = "Log10 (Adjusted Odds Ratio)"
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, main = "Adjusted Odds Ratio")
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box(bty="l")
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lines(density(log10(merged_df3$or_kin), na.rm = T, bw = "nrd0") # default
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, col = "black"
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, lwd = 2)
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#--------------------
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# logistic OR: raw
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#-------------------
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#ylim_or_logistic = max(density(merged_df3$or_logistic, na.rm = T)$y)
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#ylim_or_logistic
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#hist(merged_df3$or_logistic
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# , prob = TRUE
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# , col = "grey"
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# , border= "black"
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# , ylim = c(0, ylim_or)
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# , xlab = "Odds Ratio"
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# , main = "Logistic Odds Ratio")
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#box(bty="l")
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#lines(density(merged_df3$or_logistic, na.rm = T, bw = "nrd0") # default
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# , col = "black"
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# , lwd = 2)
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#plot(density(merged_df3$or_logistic, na.rm = T, bw = "nrd0"))
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######################################################################
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#==================
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# Foldx and DUET
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#==================
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par(mfrow = c(2,2))
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#-----------------
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# Foldx: scaled
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#-----------------
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ylim_foldx = max(density(merged_df3$ddg, na.rm = T)$y)
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ylim_foldx
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hist(merged_df3$ddg
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, prob = TRUE
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, col = "grey"
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, border= "black"
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, ylim = c(0, ylim_foldx )
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, xlab = "Foldx ddg"
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, main = "Foldx")
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box(bty="l")
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lines(density(merged_df3$ddg, na.rm = T, bw = "nrd0") # default
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, col = "black"
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, lwd = 2)
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#-----------------
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# Foldx: scaled
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#-----------------
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ylim_foldx_scaled = max(density(merged_df3$foldx_scaled, na.rm = T)$y)
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ylim_foldx_scaled
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hist(merged_df3$foldx_scaled
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, prob = TRUE
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, col = "grey"
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, border= "black"
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, ylim = c(0, ylim_foldx_scaled)
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, xlab = "Foldx ddg scaled"
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, main = "Foldx")
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box(bty="l")
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lines(density(merged_df3$foldx_scaled, na.rm = T, bw = "nrd0") # default
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, col = "black"
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, lwd = 2)
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#===============================================================
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#-------------
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# DUET: raw
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#-------------
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ylim_duet = max(density(merged_df3$duet_stability_change, na.rm = T)$y)
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ylim_duet
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hist(merged_df3$duet_stability_change
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, prob = TRUE
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, col = "grey"
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, border= "black"
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, ylim = c(0, ylim_duet )
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, xlab = "DUET ddg"
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, main = "DUET ")
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box(bty="l")
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lines(density(merged_df3$duet_stability_change, na.rm = T, bw = "nrd0") # default
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, col = "black"
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, lwd = 2)
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#---------------
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# DUET: scaled
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#---------------
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ylim_duet_scaled = max(density(merged_df3$duet_scaled, na.rm = T)$y)
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ylim_duet_scaled
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hist(merged_df3$duet_scaled
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, prob = TRUE
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, col = "grey"
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, border= "black"
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, ylim = c(0, ylim_duet_scaled)
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, xlab = "DUET ddg scaled"
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, main = "DUET")
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box(bty="l")
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lines(density(merged_df3$duet_scaled, na.rm = T, bw = "nrd0") # default
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, col = "black"
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, lwd = 2)
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###################
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summary(merged_df3$duet_stability_change)
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range(merged_df3$duet_stability_change)
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summary(merged_df3$ddg)
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range(merged_df3$ddg)
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foldx_seq = seq(min(merged_df3$ddg), max(merged_df3$ddg))
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length(foldx_seq)
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duet_seq = seq(min(merged_df3$duet_stability_change), max(merged_df3$duet_stability_change))
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duet_seq
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wilcox.test(merged_df3$duet_stability_change
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, merged_df3$ddg
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, paired = T)
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boxplot(merged_df3$duet_stability_change
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, merged_df3$ddg)
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# scaled
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summary(merged_df3$foldx_scaled)
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foldx_seq_scaled = seq(min(merged_df3$foldx_scaled)
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, max(merged_df3$foldx_scaled))
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length(foldx_seq_scaled)
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summary(merged_df3$duet_scaled)
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duet_seq_scaled = seq(min(merged_df3$duet_scaled)
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, max(merged_df3$duet_scaled))
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length(duet_seq_scaled)
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#=====================
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# corr with mutaton class
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table(merged_df3$mutation_info)
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merged_df3$mutation_info_categ = ifelse(merged_df3$mutation_info == dr_muts_col, 1, 0)
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table(merged_df3$mutation_info_categ)
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table(merged_df3$mutation_info)
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merged_df3$mutation_info_categ = ifelse(merged_df3$mutation_info == dr_muts_col, 1, 0)
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table(merged_df3$mutation_info_categ)
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cor.test(merged_df3$mutation_info_categ, merged_df3$duet_scaled, method = "spearman")
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cor.test(merged_df3$mutation_info_categ, merged_df3$foldx_scaled, method = "spearman")
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cor.test(merged_df3$duet_scaled, merged_df3$foldx_scaled, method = "spearman")
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cor.test(merged_df3$duet_scaled, merged_df3$af, method = "spearman")
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# normality test
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#P-value > 0.05: we can assume the normality.
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shapiro.test(merged_df3$or_mychisq)
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shapiro.test(log10(merged_df3$or_mychisq))
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shapiro.test(merged_df3$or_kin)
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shapiro.test(merged_df3$duet_stability_change)
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shapiro.test(merged_df3$ddg)
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shapiro.test(merged_df3$duet_scaled)
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shapiro.test(merged_df3$foldx_scaled)
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summary(merged_df3$or_kin)
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summary(log10(merged_df3$or_mychisq))
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table(merged_df3$or_mychisq > 1)
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table(log10(merged_df3$or_mychisq > 1))
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# percentage
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(table(merged_df3$or_mychisq > 1)[[2]]/sum(table(merged_df3$or_mychisq > 1))*100)
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(table(merged_df3$or_kin > 1)[[2]]/sum(table(merged_df3$or_kin > 1))*100)
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