Software to generate the figures for the study "The distinct roles of genome, methylation, transcription, and translation on protein expression in Arabidopsis thaliana resolve the Central Dogma's information flow"

This compressed tarball contains an R Markdown file and R scripts and datasets that when executed (knitted) in RStudio will reproducibly create all the main figures in the paper Revisiting the Central Dogma: the distinct roles of genome, methylation, transcription, and translation on protein expression in Arabidopsis thaliana [except Fig1 (composite) and Fig 12 (manually created)], and perform the correlation and modelling analyses presented in the paper.

To run the Code, 

1. You will require RStudio and have installed the following R packages

 
    library(knitr)
  library(corrplot)
  library(ggplot2)
  library(ggExtra)
  library(cowplot)
  library(kableExtra)
  library(bookdown)
  library(ggpmisc)
  library(forcats)
  library(scales)
  library(grid)
  library(forcats)
  library(ggvenn)
  library(ggpubr)
  library(ggVennDiagram)
  library(eulerr)
  library(ggplotify)
  library(forestplot)
  library(dplyr)
  library(reshape)
  library(ggh4x)
  

2. Create a working directory, Copy the compressed tar ball col-can-v2.tar.gz into directory and extract the archive with the command 

tar xzvf col-can-v2.tar.gz

You shoudl get the output:

% tar xzvf col-can-v2.tar.gz
x col-can-figures.Rmd
x col-can.functions.R
x gff.R
x ./Data/
x ./Data/Col.combined.RData
x ./Data/Can.combined.RData
x ./Data/RiboseqColasReference_kallisto.gene.Can_vs_Col.edgeR.DE_results.txt
x ./Data/col-can-orthologs.txt
x ./Data/anticodon.txt
x ./Data/GtRNAdb_Gene_Symbol_TAIR10_coordinate.csv
x ./Data/Col_gene_level_methylation_Can_withColRef_kallisto.gene.TPM.not_cross_norm.txt
x ./Data/HOG_gene_1to1_plus_reciprocal_duplicated_annotation.txt
x ./Data/240823_ColCan_founder_iBAQ(uni)_v3.txt
x ./Data/Can.codon.usage.RData
x ./Data/kallisto.gene.counts.matrix.Can_vs_Col.edgeR.DE_results
x ./Data/Anticodons.txt
x ./Data/Col.codon.usage.RData
x ./Data/col_can_dnadiff_rescaled.csv
x ./Data/Col_Can_all_combined_09112024.RData
x ./Data/Col.gff3
x ./Data/cyto.isodecoders.txt
x ./Data/Clean_230207_Col_vs_Can_proteome_TMT_newID.16032024.txt
x ./Data/Col_gene_level_methylation_sum.txt
x ./Data/orthologs.transcripts.txt
x ./Data/Can.gff3
x ./Data/240423_iBAQ_ColCan_founder_DIA60min_v2.txt

3. In RStudio, load the R markdown file  col-can-figures.Rmd and press the "Knit" button. The code will execute and crease a new subdirectory "./Output" containing the output figures. It also generates a PDF col-can-figures.pdf containing supplementary figures and tables.