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aomic-skill

Orchestrates AOMIC dataset download, BIDS staging, phenotype extraction, and multimodal MRI processing.

89|5|Updated Mar 25, 2026
Search Tags:#quality control#data staging#neuroimaging#fmri#bids#phenotype extraction#aomic
One-click install
npx skills add https://github.com/CUHK-AIM-Group/NeuroDiscovery --skill aomic-skill-cuhk-aim-group
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aomic-skill
Source: https://github.com/CUHK-AIM-Group/NeuroDiscovery/tree/main/skills/aomic-skill
Command: npx skills add https://github.com/CUHK-AIM-Group/NeuroDiscovery --skill aomic-skill-cuhk-aim-group

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, and includes scripts (resource) components.

What problem does it solve? Working with the AOMIC (Amsterdam Open MRI Collection) dataset requires coordinating data download, BIDS-compliant organization, phenotype table merging, and modality-specific MRI processing across multiple tools. This Skill provides a single orchestration layer that manages the entire workflow so researchers do not have to manually wire together staging scripts, phenotype extraction, and sMRI/fMRI pipelines. ## Core Features & Use Cases - BIDS Staging and Validation: Validates and reorganizes raw AOMIC subject directories into BIDS-compliant layouts with sidecar preservation, dataset_description.json, and participants.tsv generation, including dry-run preview mode. - Phenotype Extraction and Merging: Merges Big Five personality, Raven's progressive matrices, and demographics tables, cross-referenced against imaging subject lists, into analysis-ready CSV files. - QC Summaries and Exclusion Lists: Combines fMRIPrep confounds (framewise displacement) and FreeSurfer recon-all metrics to produce per-subject QC reports with configurable exclusion thresholds. - Use Case: A researcher downloads AOMIC-ID1000 and needs the full cohort staged into BIDS format, phenotypes merged for only subjects with imaging data, and QC exclusion lists generated before running connectivity analysis. ## Quick Start Ask the agent to stage the local AOMIC raw data into a BIDS-compliant dataset and generate the participants metadata under aomic_output/bids.

Frequently Asked Questions about aomic-skill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I organize AOMIC data into BIDS format?▼

Run the reorganize_aomic.py script with --input pointing to your raw AOMIC directory and --output for the BIDS destination. It validates subject IDs, routes T1w and BOLD files to anat/ and func/ folders, preserves JSON sidecars, and generates dataset_description.json and participants.tsv. Use --dry-run to preview first.

How to merge AOMIC phenotype tables with imaging subject lists?▼

Use extract_aomic_phenotype.py with --phenotype-dir pointing to the phenotype CSV/TSV files and --imaging-ids pointing to a BIDS participants.tsv. It merges Big Five, Raven's, and demographics tables on subject_id and filters to subjects present in both imaging and phenotype data.

What AOMIC sub-datasets are supported?▼

The workflow supports AOMIC-ID1000 (about 1,000 participants with T1w, resting-state, and four task fMRI paradigms), AOMIC-PIOP1, and AOMIC-PIOP2. Each has slightly different task paradigms and phenotype measures, which the staging script handles via a --sub-dataset parameter.

How is motion-based exclusion done for AOMIC fMRI data?▼

The aomic_qc_summary.py script reads fMRIPrep confounds files and computes mean and max framewise displacement per subject. Subjects exceeding the mean FD threshold (default 0.3 mm) or max FD threshold (default 5.0 mm) are flagged in the exclusion list with reasons.

Does the AOMIC staging script modify my original raw data?▼

No. By default the script runs in validation-only mode without copying anything. Copying only occurs when you explicitly pass --copy, and existing destination files are skipped rather than overwritten. A --dry-run mode previews all planned operations.

When should I use the narrow staging path instead of full orchestration?▼

Use the narrow path when the task only requires reorganizing local raw AOMIC files into BIDS layout without preprocessing, phenotype merging, or downstream analysis. The full orchestration workflow with download and modality delegation is only needed for end-to-end multimodal processing requests.

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