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Examples

These examples are intended to be copied and adjusted for a project. Use --metadata-only first to inspect the manifest before downloading large files.

Find BRD4 TF ChIP-seq FASTQs

encodefetch \
  --assay-title "TF ChIP-seq" \
  --target-label BRD4 \
  --organism "Homo sapiens" \
  --file-type fastq \
  --metadata-only \
  --nfcore \
  --snakemake

Download the same dataset

encodefetch \
  --assay-title "TF ChIP-seq" \
  --target-label BRD4 \
  --organism "Homo sapiens" \
  --file-type fastq \
  --progress \
  --threads 8 \
  --nfcore \
  --snakemake

Metadata and nf-core samplesheet only

encodefetch \
  --assay-title "TF ChIP-seq" \
  --target-label BRD4 \
  --file-type fastq \
  --metadata-only \
  --nfcore \
  --control-strategy best

Use --control-strategy first for deterministic first-control selection, all to duplicate case rows once per control, or pool to keep one case row with semicolon-separated controls.

Accessions mode

encodefetch \
  --accessions ENCSR514EOE,ENCSR395MHA \
  --file-type fastq \
  --metadata-only \
  --progress

Accessions file mode

encodefetch \
  --accessions accessions.txt \
  --file-type fastq \
  --metadata-only \
  --nfcore

encodefetch \
  --assay-title "TF ChIP-seq" \
  --target-label BRD4 \
  --target-label SMAD3 \
  --organism "Homo sapiens" \
  --perturbed false \
  --file-type fastq \
  --metadata-only

encodefetch \
  --assay-title "RNA-seq" \
  --series OrganismDevelopmentSeries \
  --file-type fastq \
  --metadata-only \
  --progress

Python exporter smoke test

import pandas as pd
from encodefetch.exporters.nfcore_chipseq import NFCoreChipseq

df = pd.DataFrame(
    [
        {
            "experiment_accession": "ENCSRCASE",
            "is_control": False,
            "matched_control_experiments": "ENCSRCTRL",
            "controlled_by_files": "ENCFFCTRL",
            "file_accession": "ENCFFCASE",
            "file_format": "fastq",
            "fastq_1": "case_R1.fastq.gz",
            "fastq_2": "case_R2.fastq.gz",
            "target_label": "BRD4",
            "biological_replicates": "1",
        },
        {
            "experiment_accession": "ENCSRCTRL",
            "is_control": True,
            "file_accession": "ENCFFCTRL",
            "file_format": "fastq",
            "fastq_1": "ctrl_R1.fastq.gz",
            "fastq_2": "ctrl_R2.fastq.gz",
            "biological_replicates": "1",
        },
    ]
)

NFCoreChipseq().write(df, "nfcore_chipseq.csv", control_strategy="all")