This repository contains scripts and files used to analyze ChIP-Seq experiments for Klasfeld et al 2022.
To generate a demo greenscreen at path demo/data/macs2_out/inputControls/qval10/merge500bp_20inputs.txt
run the following command in the current working directory:
python3 scripts/greenscreenPipeline.py \
-c Chr2 --genome_prefix TAIR10_Chr2 \
--trimmomatic_params "LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36" \
--bowtie2_index_dir demo/meta/ArabidopsisGenome/bowtie2_genome_dir \
--chipqc_samplesheet_dir demo/meta \
demo/meta/input_meta.csv \
demo/meta/ArabidopsisGenome/TAIR10_Chr2.fasta \
demo/meta/ArabidopsisGenome/Araport11_GFF3_genes_transposons.UPDATED.201606.Chr2.gff \
demo/meta/ArabidopsisGenome/TAIR10_Chr2_count.txt \
demo/data
A docker image to run this repository can be pulled using the following command:
docker pull sklasfeld/greenscreen:latest
A more detailed tutorial to run the greenscreen pipeline is found in TUTORIAL.pdf
data
directory includes- Arabidopsis blacklist
- Arabidopsis greenscreen
- other analysis results
notebook
directory: jupyter notebooks used to generate some of the plots for the papermeta
directory: text files used for providing context for running specific scripts- See TUTORIAL.pdf and meta/README.md for more information about specific files
scripts
directory: custom scripts used for greenscreen and ChIP-Seq analysis- See TUTORIAL.pdf and scripts/README.md for more information about specific files
demo
directory: input files to run demo scriptscripts/greenscreenPipeline.py