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List workflows · mkurman | DecimalAI

scienceby mkurman

List workflows

mkurman/deeptools

Source mkurman/zorai ↗License MIT

NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.

SkillScore91Maintained

Automatic

Research pack

Last verified 8/21/2026

What it changes

Passed 20 of 22 test cases with the skill, and 17 of 22 without it.

Without skill77%

With skill91%

Checks it passed that the model alone missed

Specifies effective genome size 142573017
Specifies effective genome size 100286401
Specifies effective genome size 2652783500

and 1 more in the full report

4 fixed16 passed either way1 still failing1 broke

Pass-rate lift: +14 pp
Tokens: +121%
Agent turns: 0%
Response time: -34%

Model gemini-3.6-flashMeasured 8/21/2026v120 of 22 cases passed with skill

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/mkurman-deeptools/SKILL.md https://app.decimal.ai/s/mkurman-deeptools/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add mkurman-deeptools, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/mkurman-deeptools/ and pins it in .decimal/skills.lock

decimalai skills add mkurman-deeptools

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/mkurman-deeptools/SKILL.md https://app.decimal.ai/s/mkurman-deeptools/SKILL.md

Raw file: /s/mkurman-deeptools/SKILL.md ↗ · machine-readable summary at /s/mkurman-deeptools.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 4

Prompt

I need to perform RPGC normalization on C. elegans (ce11) sequencing data. What effective genome size numerical value should I pass to the coverage tool?

What was checked, without and with the skill
Checked	Without skill	With skill
Specifies effective genome size 100286401	Missed	Passed

case-04 · gemini-3.6-flash · 8/21/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md301 lines8 filesincludes scripts

----|----------|------|-------| | Human | GRCh38/hg38 | 2,913,022,398 | --effectiveGenomeSize 2913022398 | | Mouse | GRCm38/mm10 | 2,652,783,500 | --effectiveGenomeSize 2652783500 | | Zebrafish | GRCz11 | 1,368,780,147 | --effectiveGenomeSize 1368780147 | | Drosophila | dm6 | 142,573,017 | --effectiveGenomeSize 142573017 | | C. elegans | ce10/ce11 | 100,286,401 | --effectiveGenomeSize 100286401 |

Complete table with read-length-specific values: references/effective_genome_sizes.md

Common Parameters Across Tools

Many deepTools commands share these options:

Performance:

--numberOfProcessors, -p: Enable parallel processing (always use available cores)
--region: Process specific regions for testing (e.g., chr1:1-1000000)

Read Filtering:

--ignoreDuplicates: Remove PCR duplicates (recommended for most analyses)
--minMappingQuality: Filter by alignment quality (e.g., --minMappingQuality 10)
--minFragmentLength / --maxFragmentLength: Fragment length bounds
--samFlagInclude / --samFlagExclude: SAM flag filtering

Read Processing:

--extendReads: Extend to fragment length (ChIP-seq: YES, RNA-seq: NO)
--centerReads: Center at fragment midpoint for sharper signals

Best Practices

File Validation

Always validate files first using scripts/validate_files.py to check:

File existence and readability
BAM indices present (.bai files)
BED format correctness
File sizes reasonable

Analysis Strategy

Start with QC: Run correlation, coverage, and fingerprint analysis before proceeding
Test on small regions: Use --region chr1:1-10000000 for parameter testing

Track record

Benchmark

20 / 22

test cases passed, vs 17 / 22 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

mkurman / zorai

skills/scientific-skills/deeptools/SKILL.md

View on GitHub ↗

License BSD licenseImported 8/3/2026Version v1Bundled 7 files · scripts

More skills from the same source and nearby in the registry, with their headline benchmark lift.