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methylation-clock【效率与协作】Compute epigenetic age from DNA methylation arrays using PyAging clocks from GEO accessions or local files.
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name: methylation-clock description: Compute epigenetic age from DNA methylation arrays using PyAging clocks from GEO accessions or local files. license: MIT metadata: version: 0.1.0 tags:
Epigenetic age workflows are difficult to reproduce because preprocessing and clock inputs differ across tools and publications. This skill standardizes a PyAging-first pipeline from ingestion to report generation, with explicit reproducibility outputs.
--geo-id) or local methylation file (--input).--geo-id (example: GSE139307)--input (.pkl, .pickle, .csv, .tsv, .csv.gz, .tsv.gz)--output--clocksDemo fixture provenance and checksum are documented in skills/methylation-clock/data/PROVENANCE.md.
Install optional methylation-clock dependency (not part of the global base requirements):
pip install pyaging>=0.1
# Demo
python skills/methylation-clock/methylation_clock.py \
--input skills/methylation-clock/data/GSE139307_small.csv.gz \
--output /tmp/methylation_clock_demo
# GEO input
python skills/methylation-clock/methylation_clock.py \
--geo-id GSE139307 \
--output /tmp/methylation_clock_geo
# Local methylation file
python skills/methylation-clock/methylation_clock.py \
--input my_methylation.pkl \
--clocks Horvath2013,AltumAge,PCGrimAge,GrimAge2,DunedinPACE \
--output /tmp/methylation_clock_local
methylation_clock_report/
├── report.md
├── figures/
│ ├── clock_distributions.png
│ └── clock_correlation.png
├── tables/
│ ├── predictions.csv
│ ├── prediction_summary.csv
│ ├── missing_features.csv
│ └── clock_metadata.json
└── reproducibility/
├── commands.sh
├── environment.yml
└── checksums.sha256
skills/methylation-clock/methylation_clock.py.rnaseq-de for transcriptomic-aging contrasts and equity-scorer for cohort context.