Sources code used in the analysis of Arabidopsis development
The shell and R scripts can be used to reproduce the processing of the RNAseq and proteomics data.
run_01.fastqc.raw.sh
(quality control of raw data)run_02.trimmomatic.sh
(trimming of sequencing adapters and low quality reads)run_03.fastqc.trimmed.sh
(quality control of trimmed data)run_04.kallisto.sh
(mapping of trimmed reads toAraport11_genes.201606.cdna.fasta.gz
, can be downloaded from here and indexed withkallisto index [arguments] FASTA-files
)run_05.txi2gene_kallisto.R
(R script to collapse transcripts to gene level)run_06.preprocessing_rna.DV.R
(R script to normalize and filter transcript data for development datasets)run_07.preprocessing_protein_DVFL.R
(R script to normalize and filter proteinGroups.txt and phospho (STY)site.txt MaxQuant output data files for flower dataset)run_08.preprocessing_protein_DVEB.R
(R script to normalize and filter proteinGroups.txt and phospho (STY)site.txt MaxQuant output data files for seed & silique dataset)run_09.preprocessing_protein_DVLF.R
(R script to normalize and filter proteinGroups.txt and phospho (STY)site.txt MaxQuant output data files for leaf dataset)