ChromActivity

ChromActivity is a computational framework for the annotation of regulatory activity genomewide, through integration of data from epigenomic maps and multiple functional characterization assays.

We generate three types of annotations:

• Expert score tracks: Genomewide regulatory activity prediction tracks associated with each functional characterization assay dataset across all cell and tissue types with epigenome data
• ChromScoreHMM annotations: Cell type specific genome annotations based on the combinatorial and spatial patterns within the expert predictions
• ChromScore tracks: Genomewide, cell type specific ensemble regulatory activity prediction tracks. Provides a numerical score for each 25 bp interval in the genome

Precomputed annotations

Precomputed annotations are available to download at: https://ucla.box.com/v/chromactivity

View annotations on the UCSC Genome Browser: session link, track hub link

Getting started

ChromActivity manages its dependencies using the conda package manager. Mambaforge is the recommended distribution for installing conda.

# Download ChromActivity from repository
git clone --depth 1 https://github.com/ernstlab/chromactivity

# Set up conda environment
cd chromactivity
conda env create -f environment.yml
conda activate chromactivity_env

# Download and extract ChromHMM
wget -N -P vendored https://ernstlab.biolchem.ucla.edu/ChromHMM/ChromHMM.zip
unzip -o vendored/ChromHMM.zip -d vendored

Raw data directories

By default, ChromActivity uses imputed epigenomic data from the Roadmap Epigenomics compendium with the following directory structure:

# Data URLs: https://egg2.wustl.edu/roadmap/web_portal/imputed.html

# Imputed signal tracks
f"data/raw/roadmap/signal/{cell_type}/{cell_type}-{mark}.imputed.pval.signal.bigwig"

# Peak calls
f"data/raw/roadmap/peaks/{cell_type}/{cell_type}-{mark}.imputed.narrowPeak.bed.nPk.gz"

# 25-State ChromHMM model
f"data/raw/roadmap/chromstate/chromstate_25/{cell_type}/{cell_type}_25_imputed12marks_mnemonics.sorted.bed",

Overriding the default directory structure is possible by modifying chromactivity/mappings.py.

Usage examples

Command line usage examples:

# Train and serialize ChromActivity experts using the default labels in "data/labels"
chromactivity train_experts --labels_dir data/labels --model_out_fn "models/my_chromactivity.model"

# Generate tracks from serialized model for the HepG2 (Roadmap epigenome ID: E118) cell type
chromactivity generate_tracks --model_fn "models/chromactivity.model" --cell_types "E118" --coords_bed_fn "data/external/test.bed" --combined_bigwigs_out_dir "tracks/"

# Generate ChromScoreHMM annotations from generated tracks
chromactivity train_chromscorehmm --num_states 15 --track_dir "tracks/" --out-dir "models/chromscorehmm"

External resources

• vendored/ChromHMM/ChromHMM.jar: https://ernstlab.biolchem.ucla.edu/ChromHMM
• data/external/hg19.chrom.sizes: https://hgdownload.soe.ucsc.edu/goldenPath/hg19/bigZips/hg19.chrom.sizes