updated logo plot data to source from combining_df_plotting.R
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1 changed files with 15 additions and 55 deletions
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@ -1,71 +1,30 @@
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#=======================================================================
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#!/usr/bin/env Rscript
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# Task: To generate a logo plot or bar plot but coloured
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#########################################################
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# aa properties.
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# TASK: producing boxplots for dr and other muts
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# step1: read mcsm file and OR 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 if you can!
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# useful links
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#########################################################
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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/workflow.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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#=======================================================================
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#%% specify curr dir
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# working dir and loading libraries
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getwd()
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getwd()
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setwd("~/git/LSHTM_analysis/plotting_test/")
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setwd("~/git/LSHTM_analysis/scripts/plotting")
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getwd()
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getwd()
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#=======================================================================
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#%% load packages
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# header file
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source("Header_TT.R")
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header_dir = "~/git/LSHTM_analysis/"
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#library(ggplot2)
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source(paste0(header_dir, "/", "my_header.R"))
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#library(data.table)
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#=======================================================================
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#library(dplyr)
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#%% variable assignment: input and output paths & filenames
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drug = "pyrazinamide"
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gene = "pncA"
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gene_match = paste0(gene,"_p.")
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cat(gene_match)
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#===========
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# data dir
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#===========
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datadir = paste0("~/git/Data")
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#===========
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#===========
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# input
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# input
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#===========
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#===========
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# source R script "combining_two_df.R"
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source("combining_dfs_plotting.R")
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#indir = paste0(datadir, "/", drug, "/", "output") # reading files
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indir = "../meta_data_analysis" # sourcing R script
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in_filename = "combining_df_ps.R"
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infile = paste0(indir, "/", in_filename)
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cat(paste0("Input is a R script: ", "\"", infile, "\"")
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, "\n========================================================")
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#===========
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#===========
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# output
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# output
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#===========
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#===========
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# 1) lineage dist of all muts
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outdir = paste0("~/git/Data", "/", drug, "/", "output/plots") #same as indir
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#cat("Output dir: ", outdir, "\n")
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#file_type = ".svg"
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#out_filename1 = paste0(tolower(gene), "_lineage_dist_ps", file_type)
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#outfile1 = paste0(outdir, "/", out_filename1)
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#cat(paste0("Output plot1 :", outfile1)
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# , "\n========================================================")
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#%% end of variable assignment for input and output files
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logo_plot = "logo_plot.svg"
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#=======================================================================
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plot_logo_plot = paste0(plotdir,"/", logo_plot)
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##%% read input file
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cat("Reading input file(sourcing R script):", in_filename)
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source(infile)
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#==========================
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#==========================
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# This will return:
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# This will return:
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@ -205,6 +164,7 @@ ggseqlogo(wide_df_logor, method="custom", seq_type="aa") + ylab("my custom heigh
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library(Logolas)
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library(Logolas)
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# data was pnca_msa.txt
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# data was pnca_msa.txt
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#FIXME: generate this file
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seqs = read.csv("~/git//Data/pyrazinamide/snp_seqsfile.txt"
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seqs = read.csv("~/git//Data/pyrazinamide/snp_seqsfile.txt"
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, header = FALSE
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, header = FALSE
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@ -217,4 +177,4 @@ logomaker(seqs, type = "EDLogo", color_type = "per_symbol"
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logomaker(seqs, type = "Logo", color_type = "per_symbol")
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logomaker(seqs, type = "Logo", color_type = "per_symbol")
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#%% end of script
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#%% end of script
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#=======================================================================
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#=======================================================================
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