/download-encode
Download ENCODE genomics files (BED, FASTQ, BAM, bigWig, etc.) to the user's machine. Use when the user wants to download data files from ENCODE experiments.
$ npx -y skills add ammawla/encode-toolkit --skill download-encode --agent claude-codeHow it fires
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/download-encode
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Download ENCODE genomics files (BED, FASTQ, BAM, bigWig, etc.) to the user's machine. Use when the user wants to download data files from ENCODE experiments.
SKILL.md
download-encode.SKILL.mdname: download-encode
description: Download ENCODE genomics files (BED, FASTQ, BAM, bigWig, etc.) to the user's machine. Use when the user wants to download data files from ENCODE experiments.
Download ENCODE Files
When to Use
- User wants to download ENCODE data files to their local machine
- User asks to "download", "get", or "fetch" ENCODE files
- User needs specific file formats (BED, FASTQ, BAM, bigWig) from experiments
- User wants to batch download files matching search criteria
- User needs to verify file integrity after download (MD5 checksums)
- User asks about organizing downloaded files by experiment or format
Help the user download ENCODE data files to their local machine.
Download Strategy
1. **Specific files by accession**: Use `encode_download_files` with file accession IDs (e.g., "ENCFF635JIA").
2. **Batch download by criteria**: Use `encode_batch_download` to search and download in one step.
- Always start with `dry_run=True` (default) to preview what will be downloaded
- Show the user the file count, total size, and file list
- Only proceed with `dry_run=False` after user confirms
3. **Download organization options**:
- `"flat"`: All files in one directory
- `"experiment"`: Organized by experiment accession (recommended)
- `"format"`: Organized by file format
- `"experiment_format"`: Organized by experiment, then format
Important Notes
- All downloads include MD5 verification by default (`verify_md5=True`)
- Ask the user for a download directory if not specified
- Warn about large downloads (>1GB total or >50 files)
- Files already downloaded will be skipped (idempotent)
- For restricted files, credentials must be configured first via `encode_manage_credentials`
Pitfalls & Edge Cases
1. **Disk space**: BAM files can be 5-50GB each; FASTQ files 1-20GB. Before any batch download, warn the user about estimated total size from the dry_run preview. A single ChIP-seq experiment can produce 10-30GB of raw data files. 2. **MD5 verification failures**: If MD5 verification fails, the file may be corrupted or incompletely downloaded. Always re-download rather than skipping verification. Never set `verify_md5=False` unless the user explicitly requests it and understands the risk. 3. **Downloading too much data**: Users often request BAM files when they only need peak calls or signal tracks. Suggest `preferred_default=True` to get ENCODE's recommended files, or filter by `output_type` (e.g., "IDR thresholded peaks", "fold change over control") to avoid downloading raw data unnecessarily. 4. **Restricted/unreleased data**: Files with status other than "released" may require ENCODE credentials. Use `encode_manage_credentials(action="check")` to verify credentials are configured before attempting to download restricted data. 5. **Mixed assemblies in batch download**: Always specify the `assembly` filter (e.g., "GRCh38") in batch downloads. Without it, you may download files aligned to different genome assemblies (hg19, GRCh38, mm10), making downstream analysis impossible. 6. **Timeout on large files**: For downloading many files or very large files, `encode_batch_download` handles retries and concurrent downloads better than individual `encode_download_files` calls. The default limit of 100 files provides a safety cap.
File Type Guide
When users request "files" without specifying a type, use this priority to suggest the right output_type:
- **Peak analysis**: `output_type="IDR thresholded peaks"` (most stringent, recommended for ChIP-seq/ATAC-seq)
- **Signal visualization**: `file_format="bigWig"`, `output_type="fold change over control"` (for genome browser tracks)
- **Gene expression**: `output_type="gene quantifications"` (for RNA-seq TPM/FPKM tables)
- **Raw data reprocessing**: `file_format="fastq"` (only when user needs to run their own pipeline)
- **Quick defaults**: `preferred_default=True` (ENCODE's recommended files for any experiment)
What to Download for Each Analysis
| Analysis Goal | File Format | Output Type | Why This File | |---|---|---|---| | Peak locations (ChIP/ATAC) | bed narrowPeak | IDR thresholded peaks | Gold-standard replicated peaks passing irreproducibility threshold | | Broad domain marks (H3K27me3) | bed broadPeak | replicated peaks | Broad marks need broadPeak format, not narrowPeak | | Signal visualization | bigWig | fold change over control | Normalized signal track for genome browser display | | Signal statistics | bigWig | signal p-value | Statistical significance of signal over background | | Raw data reprocessing | fastq | reads | Starting from scratch with your own pipeline | | Alignment inspection | bam | alignments | Check read mapping quality, fragment sizes, duplicates | | Browser-compatible peaks | bigBed | peaks | UCSC/IGV-compatible binary peak format | | Gene expression levels | tsv | gene quantifications | TPM/FPKM tables for RNA-seq differential expression | | Transcript isoforms | tsv | transcript quantifications | Isoform-level expression for splicing analysis | | 3D genome contacts | hic | contact matrix | Hi-C interaction matrices for loop/TAD calling | | Methylation levels | bed | methylation state at CpG | Per-CpG methylation fractions for WGBS |
Assay-Specific Recommendations
| Assay | Primary Download | Secondary Download | |---|---|---| | Histone ChIP-seq | IDR thresholded peaks (bed) | fold change over control (bigWig) | | TF ChIP-seq | IDR thresholded peaks (bed) | fold change over control (bigWig) | | ATAC-seq | IDR thresholded peaks (bed) | fold change over control (bigWig) | | DNase-seq | peaks (bed) | signal of unique reads (bigWig) | | RNA-seq | gene quantifications (tsv) | signal of unique reads (bigWig) | | WGBS | methylation state at CpG (bed) | signal (bigWig) | | Hi-C | contact matrix (hic) | contact domains (bed) | | CUT&RUN | peaks (bed) | fold change over control (bigWig) | | CUT&Tag | peaks (bed) | fold change over control (bigWig) | | eCLIP
Read more
name: download-encode description: Download ENCODE genomics files (BED, FASTQ, BAM, bigWig, etc.) to the user's machine. Use when the user wants to download data files from ENCODE experiments.
Download ENCODE Files
When to Use
- User wants to download ENCODE data files to their local machine
- User asks to "download", "get", or "fetch" ENCODE files
- User needs specific file formats (BED, FASTQ, BAM, bigWig) from experiments
- User wants to batch download files matching search criteria
- User needs to verify file integrity after download (MD5 checksums)
- User asks about organizing downloaded files by experiment or format
Help the user download ENCODE data files to their local machine.
Download Strategy
1. **Specific files by accession**: Use `encode_download_files` with file accession IDs (e.g., "ENCFF635JIA").
2. **Batch download by criteria**: Use `encode_batch_download` to search and download in one step.
- Always start with `dry_run=True` (default) to preview what will be downloaded
- Show the user the file count, total size, and file list
- Only proceed with `dry_run=False` after user confirms
3. **Download organization options**:
- `"flat"`: All files in one directory
- `"experiment"`: Organized by experiment accession (recommended)
- `"format"`: Organized by file format
- `"experiment_format"`: Organized by experiment, then format
Important Notes
- All downloads include MD5 verification by default (`verify_md5=True`)
- Ask the user for a download directory if not specified
- Warn about large downloads (>1GB total or >50 files)
- Files already downloaded will be skipped (idempotent)
- For restricted files, credentials must be configured first via `encode_manage_credentials`
Pitfalls & Edge Cases
1. **Disk space**: BAM files can be 5-50GB each; FASTQ files 1-20GB. Before any batch download, warn the user about estimated total size from the dry_run preview. A single ChIP-seq experiment can produce 10-30GB of raw data files. 2. **MD5 verification failures**: If MD5 verification fails, the file may be corrupted or incompletely downloaded. Always re-download rather than skipping verification. Never set `verify_md5=False` unless the user explicitly requests it and understands the risk. 3. **Downloading too much data**: Users often request BAM files when they only need peak calls or signal tracks. Suggest `preferred_default=True` to get ENCODE's recommended files, or filter by `output_type` (e.g., "IDR thresholded peaks", "fold change over control") to avoid downloading raw data unnecessarily. 4. **Restricted/unreleased data**: Files with status other than "released" may require ENCODE credentials. Use `encode_manage_credentials(action="check")` to verify credentials are configured before attempting to download restricted data. 5. **Mixed assemblies in batch download**: Always specify the `assembly` filter (e.g., "GRCh38") in batch downloads. Without it, you may download files aligned to different genome assemblies (hg19, GRCh38, mm10), making downstream analysis impossible. 6. **Timeout on large files**: For downloading many files or very large files, `encode_batch_download` handles retries and concurrent downloads better than individual `encode_download_files` calls. The default limit of 100 files provides a safety cap.
File Type Guide
When users request "files" without specifying a type, use this priority to suggest the right output_type:
- **Peak analysis**: `output_type="IDR thresholded peaks"` (most stringent, recommended for ChIP-seq/ATAC-seq)
- **Signal visualization**: `file_format="bigWig"`, `output_type="fold change over control"` (for genome browser tracks)
- **Gene expression**: `output_type="gene quantifications"` (for RNA-seq TPM/FPKM tables)
- **Raw data reprocessing**: `file_format="fastq"` (only when user needs to run their own pipeline)
- **Quick defaults**: `preferred_default=True` (ENCODE's recommended files for any experiment)
What to Download for Each Analysis
| Analysis Goal | File Format | Output Type | Why This File | |---|---|---|---| | Peak locations (ChIP/ATAC) | bed narrowPeak | IDR thresholded peaks | Gold-standard replicated peaks passing irreproducibility threshold | | Broad domain marks (H3K27me3) | bed broadPeak | replicated peaks | Broad marks need broadPeak format, not narrowPeak | | Signal visualization | bigWig | fold change over control | Normalized signal track for genome browser display | | Signal statistics | bigWig | signal p-value | Statistical significance of signal over background | | Raw data reprocessing | fastq | reads | Starting from scratch with your own pipeline | | Alignment inspection | bam | alignments | Check read mapping quality, fragment sizes, duplicates | | Browser-compatible peaks | bigBed | peaks | UCSC/IGV-compatible binary peak format | | Gene expression levels | tsv | gene quantifications | TPM/FPKM tables for RNA-seq differential expression | | Transcript isoforms | tsv | transcript quantifications | Isoform-level expression for splicing analysis | | 3D genome contacts | hic | contact matrix | Hi-C interaction matrices for loop/TAD calling | | Methylation levels | bed | methylation state at CpG | Per-CpG methylation fractions for WGBS |
Assay-Specific Recommendations
| Assay | Primary Download | Secondary Download | |---|---|---| | Histone ChIP-seq | IDR thresholded peaks (bed) | fold change over control (bigWig) | | TF ChIP-seq | IDR thresholded peaks (bed) | fold change over control (bigWig) | | ATAC-seq | IDR thresholded peaks (bed) | fold change over control (bigWig) | | DNase-seq | peaks (bed) | signal of unique reads (bigWig) | | RNA-seq | gene quantifications (tsv) | signal of unique reads (bigWig) | | WGBS | methylation state at CpG (bed) | signal (bigWig) | | Hi-C | contact matrix (hic) | contact domains (bed) | | CUT&RUN | peaks (bed) | fold change over control (bigWig) | | CUT&Tag | peaks (bed) | fold change over control (bigWig) | | eCLIP
Showing the first part of this file.
Search ENCODE, cross-reference 14 databases, run 7 analysis pipelines, and generate publication-ready methods — all from natural language in Claude Code.
Repo: ammawla/encode-toolkit
Other skills on encode-toolkit.
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Build comprehensive chromatin accessibility maps by aggregating ATAC-seq and DNase-seq narrowPeak data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is chromatin accessible in my tissue?" by combining peak calls into a union peak
Open skill - /batch-analysis
Guide for multi-experiment batch operations: QC screening, batch download, comparison, and report generation across many ENCODE experiments simultaneously. Use when users need to process 5+ experiments together, create experiment comparison tables, perform batch quality checks,
Open skill - /bioinformatics-installer
Install bioinformatics tools for ENCODE data analysis. Covers CLI tools (BWA, STAR, samtools, MACS2), R/Bioconductor packages (DESeq2, Seurat, ChIPseeker), Python packages (Scanpy, deeptools), and Nextflow pipeline infrastructure. Generates conda environments, R install scripts,
Open skill - /cellxgene-context
Guide for integrating CellxGene Census single-cell data with ENCODE bulk experiments. Use when users need cell-type-specific expression context for ENCODE regulatory data, want to deconvolve bulk ENCODE signals, or validate regulatory elements at single-cell resolution. Trigger
Open skill - /cite-encode
Generate proper ENCODE citations for publications, grants, and presentations. Use when the user needs to cite ENCODE data, create bibliography entries, write acknowledgment sections, or ensure compliance with ENCODE data use policy.
Open skill - /clinvar-annotation
Guide for annotating ENCODE regulatory variants with ClinVar clinical significance. Use when users need to check if variants in ENCODE peaks have clinical associations, find pathogenic variants in regulatory regions, or assess variant clinical impact. Trigger on: ClinVar,
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