encodefetch 0.3.0

ENCODEfetch: a command-line tool for retrieving matched case-control data and standardized metadata from ENCODE

ENCODEfetch

ENCODEfetch is a command-line tool and Python package for retrieving matched case–control datasets and standardized metadata from the ENCODE Project.

ENCODEfetch automates:

• Search for ENCODE experiments by assay, target, organism, status, and more
• Get case-control matched experiments
• File retrieval (FASTQ, BAM, BED, bigWig, etc.) with filtering by status/assembly
• Parallel downloads files with resumable transfers and interactive progress bars.
• Standardized metadata outputs (manifest.tsv, metadata.jsonl).
• Plug-and-play samplesheets for nf-core and Snakemake workflows for reproduciable analysis.
• Interactive API returning tidy pandas.DataFrame objects of metadata with file paths for downstream analysis.

🚀 Installation

From PyPI (recommended)

pip install encodefetch

From source

git clone https://github.com/khan-lab/ENCODEfetch.git
cd ENCODEfetch
pip install -e .

Requires Python 3.9+. or newer versions.

🔧 Command-line usage

encodefetch --assay-title "TF ChIP-seq" \
             --target-label BRD4,SMAD3 \
             --organism "Homo sapiens" \
             --file-type fastq \
             --status released \
             --progress \
             --download \
             --threads 8 \
             --nfcore

Key options

• --accessions ENCSR123ABC,ENCSR456DEF — fetch experiments by accession directly.
• --accessions accessions.txt — read one experiment accession per line; blank lines and # comments are ignored.
• --assay-title — e.g. TF ChIP-seq, Histone ChIP-seq, ATAC-seq, RNA-seq.
• --target-label — one or more targets (comma-separated).
• --organism — e.g. Homo sapiens, Mus musculus.
• --file-type — restrict formats (fastq, bam, bed, bigWig…).
• --status — default released (can also include archived).
• --perturbed true|false — filter perturbed experiments.
• --download — actually download matched files.
• --threads — number of worker threads for metadata fetching, control fetching, and downloads.
• --max-retries / --chunk-size — tune download retry count and streamed chunk size.
• --nfcore / --snakemake — export pipeline-ready sample sheets.
• --control-strategy all|pool|best — choose how samplesheets represent multiple controls.

Run encodefetch --help to see all options.

📦 Outputs

After a run, outdir/ contains:

• manifest.tsv — tidy table of case/control files with metadata.
• metadata.jsonl — raw record dump (one JSON per line).
• files/ — downloaded files, organized by experiment/control.
• nfcore_*_samplesheet.csv — optional nf-core samplesheet.
• snakemake_samples.tsv — optional Snakemake sample table.

ENCODEfetch preserves all experiment-level controls in matched_control_experiments. File-level controlled_by links are normalized into controlled_by_files when ENCODE provides them. Samplesheets prefer file-level control mappings, then fall back to experiment-level controls; --control-strategy all duplicates case rows per control, pool joins controls with semicolons, and best currently chooses the first control deterministically.

🐍 Python API

import encodefetch as ef

# Search experiments
metadata, recs = ef.search_experiments(
    assay_title="TF ChIP-seq",
    target_labels=["BRD4","SMAD3"],
    organism="Homo sapiens",
    file_types={"fastq"},
    status="released",
    progress=False,
    threads=2,
)

metadata.head()

# Collapse paired-end FASTQs to one row
metadata_collapse = ef.collapse_fastq_pairs(metadata)

# Write nf-core samplesheet
ef.write_nfcore_sheet(metadata_collapse, "nfcore_chipseq.csv")

🧬 Assay support

ENCODEfetch currently provides assay-aware normalization and exporters to nf-core/snakemake samplesheets for:

• ChIP-seq (production)
• ATAC-seq (in beta)
• RNA-seq (in beta)
• more to be added ..

Each assay can plug in its own normalization (e.g., FASTQ collapsing, strandedness detection) and samplesheet exporters.

🤝 Contributing

Contributions are welcome!

• Add new assay classes under encodefetch/assays/.
• Add new exporters under encodefetch/exporters/.
• Extend metadata fields in build_file_record.

See CONTRIBUTING.md for details.