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Tooluniverse Multi Omics Integration

Checked
mims-harvard·vlatest·other·Apache-2.0

Integrates diverse multi-omics datasets (genomics, proteomics, metabolomics) for comprehensive biological insights and hypothesis generation.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add mims-harvard/tooluniverse --skill tooluniverse-multi-omics-integration -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

mims-harvard

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

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  • No pipe-to-shell installers: passed

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    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned mims-harvard/tooluniverse at f5c37eebeb.

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Commit
f5c37eebeb
Manifest
skills/tooluniverse-multi-omics-integration/SKILL.md
Scanned
6 files, 1,326 lines
Copies in repo
3 — all of them scanned
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About this skill

What it does

This skill enables AI agents to integrate and analyze multi-omics datasets, combining information from genomics, transcriptomics, proteomics, and metabolomics into a unified view. It facilitates the discovery of complex biological relationships by processing diverse data types simultaneously.

When to use it

  • Investigating disease mechanisms where genetic mutations correlate with protein expression changes.
  • Identifying biomarkers that span multiple molecular layers for more accurate diagnostics.
  • Conducting systems biology research to model cellular responses under varying environmental conditions.
  • Validating drug targets by cross-referencing genomic variants with metabolic pathway disruptions.

Key capabilities

  • Aggregates data from distinct omics domains (genomics, transcriptomics, proteomics, metabolomics).
  • Performs integrated analysis to uncover correlations across molecular layers.
  • Supports complex biological queries requiring multi-modal data synthesis.

Example prompts

  • "Analyze the correlation between specific gene mutations and downstream protein expression levels in this cancer dataset."
  • "Identify metabolic pathways that are disrupted when a particular transcriptomic signature is present."
  • "Generate a unified report linking genomic variants to metabolite concentrations for patient stratification."

Tips & gotchas

Ensure your input datasets are properly normalized and aligned before integration, as discrepancies in data formats can hinder analysis. This skill is best suited for researchers with a background in bioinformatics who understand the nuances of multi-omics data interpretation.