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Agent skill

Bulkrna Coexpression

by TianGzlab in TianGzlab/OmicsClaw

Load when discovering bulk gene co-expression modules and hub genes with R WGCNA.

Apache-2.0Auto-check passedResearch & Science

Install Bulkrna Coexpression

skills CLI
$ npx skills add TianGzlab/OmicsClaw --skill bulkrna-coexpression -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install TianGzlab/OmicsClaw bulkrna-coexpression --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/bulkrna/bulkrna-coexpression .claude/skills/bulkrna-coexpression && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
bulkrna-coexpression
GitHub stars
161
Token cost
~1.3k tokens
SKILL.md length
510 words
Files
11 (incl. references)
Skills in repo
88
Repo updated
First seen
Licence
Apache-2.0

At a glance

Load when discovering bulk gene co-expression modules and hub genes with R WGCNA.

  • Tasks that involve Bioinformatics
  • SKILL.md covers When to use, Use from a step, API and Methods and parameters, plus 5 more sections
  • Runs Python and R scripts from its folder; calls python
  • Tasks that involve DataFrames

What it does

Bulkrna Coexpression is an agent skill from TianGzlab/OmicsClaw. Load when discovering bulk gene co-expression modules and hub genes with R WGCNA. Skip direct expression contrasts (use bulkrna-de), existing-gene-list PPI lookup (use bulkrna-ppi-network), or single-cell networks (use sc-grn).

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including reference files (for example `_api.py`, `bulkrna_coexpression.py` and `examples/example_step.py`).

It sits in Research & Science, covering Bioinformatics and DataFrames. The repository describes itself as: Conversational & memory-enabled AI research partner for multi-omics analysis. CLI + Desktop App (installers in Releases). From biological idea to full research paper. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Bioinformatics
  • Tasks that involve DataFrames

Example prompts

  • “/bulkrna-coexpression”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 90a3bec. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python and R), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bulkrna Coexpression loads about 1.3k tokens when it runs, and up to ~1.8k if it reads all its reference files. Until then it costs about 62 tokens; SKILL.md has 510 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~62
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from TianGzlab/OmicsClaw at commit 90a3bec, republished under its Apache-2.0 licence (© TianGzlab). 510 words, ~1,301 tokens.

Download SKILL.mdSave it as .claude/skills/bulkrna-coexpression/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.
name
bulkrna-coexpression
description
Load when discovering bulk gene co-expression modules and hub genes with R WGCNA. Skip direct expression contrasts (use bulkrna-de), existing-gene-list PPI lookup (use bulkrna-ppi-network), or single-cell networks (use sc-grn).
trigger
coexpression, WGCNA, gene network, co-expression modules, hub genes, gene modules
tags
bulkrna, coexpression, WGCNA, network, modules, hub-genes

bulkrna-coexpression

When to use

Load when discovering bulk gene co-expression modules and hub genes with R WGCNA. Skip direct expression contrasts (use bulkrna-de), existing-gene-list PPI lookup (use bulkrna-ppi-network), or single-cell networks (use sc-grn).

Use from a step

python
from skills._sdk.notebook import load_skill, write_output
library = load_skill("bulkrna-coexpression")
result = library.analyze(data, power=6, min_module_size=10)
write_output(result, "tables/result.csv")
write_output(library.module_sizes_figure(result), "figures/result.png")

Read expression and metadata with read_input before calling the library. examples/example_step.py constructs a small synthetic dataset and checks its results through the step runner and fresh-kernel replay.

API

<!-- api:begin generated from _api.py; regenerate with run.py api <skill dir> --write -->
analyze(data: pd.DataFrame, *, power: int | None=None, min_module_size: int=10, random_state: int=54321) -> pd.DataFrame

Return R WGCNA gene-module assignments, leaving expression unchanged.

:param data: Nonnegative feature-by-sample expression; provide normalized data on the intended correlation scale. :param power: CLI default None selects the soft threshold; set a positive integer to override it. :param min_module_size: CLI default 10 genes per module. :param random_state: WGCNA blockwiseModules default seed 54321; fixes its preclustering. :returns: Gene/module DataFrame with diagnostics, hub genes and threshold fit in attrs. :raises ValueError: Input, sample count, power or module size is invalid. :raises ImportError: R WGCNA or Matrix is unavailable. :raises RuntimeError: R analysis fails.

run_info(data: pd.DataFrame, *, keep: bool=True) -> dict

Return WGCNA method diagnostics and summary.

:param data: Result from analyze. :param keep: Keep diagnostics by default; the CLI passes False. :returns: Independent diagnostics dictionary. :raises ValueError: No WGCNA diagnostics are present.

threshold_fit(data: pd.DataFrame) -> pd.DataFrame

Return the signed scale-free fit for each tested soft threshold.

:param data: Result from analyze. :returns: Table containing power, r_squared and mean_connectivity. :raises ValueError: No fit table is stored.

hub_genes(data: pd.DataFrame) -> pd.DataFrame

Return the highest absolute module-membership genes per non-grey module.

:param data: Result from analyze. :returns: Table with gene, module and kME columns. :raises ValueError: No hub table is stored.

module_sizes_figure(data: pd.DataFrame)

Plot assignment counts, including grey unassigned genes.

:param data: Gene/module table from analyze. :returns: Matplotlib Figure. :raises ValueError: The module column is missing.

<!-- api:end -->
Show full SKILL.md (218 more words)Show less

Methods and parameters

The function library returns DataFrames and Figures. The CLI loads the same library and owns reports and file writes. R runs in a temporary directory using Matrix Market, feature/sample identifiers and metadata. No R intermediate is a permanent CLI output.

Gotchas

  • analyze requires R WGCNA and Matrix, at least eight samples, and finite nonnegative expression. Cohorts with fewer than 15 samples emit a warning.
  • analyze(power=None) selects a soft threshold; an explicit power is honored. Integer matrices are converted to double for WGCNA.
  • run_info()["filtered_genes"] lists genes removed by WGCNA quality checks. Grey is unassigned; module IDs are color strings.
  • hub_genes ranks absolute module membership within each non-grey module. This is correlation evidence, not proof of regulation.
  • threshold_fit reports signed scale-free R-squared and connectivity. The correlation analysis uses the supplied expression scale; normalize upstream as needed.
  • analyze(random_state=54321) preserves the WGCNA default seed and uses one R thread. No Python module-detection fallback is used.

Inputs and outputs

Expression CSV with genes in the first column and samples in the remaining columns. The API takes that gene column as the DataFrame index.

CLI outputs:

  • tables/module_assignments.csv
  • tables/hub_genes.csv
  • tables/threshold_fit.csv
  • figures/scale_free_fit.png
  • figures/module_sizes.png
  • figures/module_dendrogram.png (assignment overview, not a dendrogram)
  • report.md, result.json
  • reproducibility/commands.sh

CLI

bash
python skills/bulkrna/bulkrna-coexpression/bulkrna_coexpression.py --demo --output /tmp/bulkrna_coexpression_demo

Run the script with --help for real-input arguments.

See also

  • references/parameters.md
  • references/methodology.md
  • references/output_contract.md

Dependencies

matplotlib, numpy, pandas, scipy, WGCNA, Matrix

© TianGzlab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 10 other files (references) in skills/bulkrna/bulkrna-coexpression of TianGzlab/OmicsClaw.

  • SKILL.md
  • _api.py
  • bulkrna_coexpression.py
  • examples/example_step.py
  • references/methodology.md
  • references/output_contract.md
  • references/parameters.md
  • rscripts/wgcna.R
  • tests/__init__.py
  • tests/test_api.py
  • tests/test_bulkrna_coexpression.py

Open the folder on GitHubat commit 90a3bec

Compare with similar skills

Bulkrna Coexpression next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Bulkrna Coexpression compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Bulkrna Coexpression this skillTianGzlab/OmicsClaw161—~1.3kAutomated safety check: PassApache-2.0
ArboretoK-Dense-AI/scientific-agent-skills48k1 repos~2.7kAutomated safety check: PassBSD-3-Clause
Bio Proteomics Spectral LibrariesGPTomics/bioSkills1.2k1 repos~4.6kAutomated safety check: PassMIT
Arboreto Grn Inferencejaechang-hits/SciAgent-Skills3702 repos~5.3kAutomated safety check: PassBSD-3-Clause
Lamindb Data Managementjaechang-hits/SciAgent-Skills3702 repos~4kAutomated safety check: PassApache-2.0
Bio Expression Matrix Sparse HandlingGPTomics/bioSkills1.2k1 repos~5.6kAutomated safety check: PassMIT

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Categories

Questions about Bulkrna Coexpression

What does Bulkrna Coexpression do?

Load when discovering bulk gene co-expression modules and hub genes with R WGCNA. Bulkrna Coexpression is an agent skill from TianGzlab/OmicsClaw. Load when discovering bulk gene co-expression modules and hub genes with R WGCNA.

When should I use Bulkrna Coexpression?

Bulkrna Coexpression fits situations like: tasks that involve Bioinformatics; tasks that involve DataFrames.

How do I install Bulkrna Coexpression in Claude Code?

Run `npx skills add TianGzlab/OmicsClaw --skill bulkrna-coexpression -a claude-code`. Or copy the skill folder (skills/bulkrna/bulkrna-coexpression in TianGzlab/OmicsClaw) into .claude/skills/bulkrna-coexpression in your project. Claude Code loads it when a task matches its description.

How do I install Bulkrna Coexpression in Codex?

Run `npx skills add TianGzlab/OmicsClaw --skill bulkrna-coexpression -a codex`. Or copy the skill folder (skills/bulkrna/bulkrna-coexpression in TianGzlab/OmicsClaw) into .agents/skills/bulkrna-coexpression in your project. Codex loads it when a task matches its description.

Can I use Bulkrna Coexpression in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add TianGzlab/OmicsClaw --skill bulkrna-coexpression -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bulkrna-coexpression, .gemini/skills/bulkrna-coexpression, .github/skills/bulkrna-coexpression and .opencode/skills/bulkrna-coexpression in your project.

What does Bulkrna Coexpression need to run?

Going by SKILL.md and its folder, Bulkrna Coexpression needs Python and R for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Bulkrna Coexpression access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Bulkrna Coexpression safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Bulkrna Coexpression use?

Bulkrna Coexpression is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Bulkrna Coexpression use?

About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 503 tokens, read only when the agent opens those files.

What are the alternatives to Bulkrna Coexpression?

Skills that share tags, products or a category with Bulkrna Coexpression: Arboreto (K-Dense-AI/scientific-agent-skills, 48k stars), Bio Proteomics Spectral Libraries (GPTomics/bioSkills, 1.2k stars), Arboreto Grn Inference (jaechang-hits/SciAgent-Skills, 370 stars) and Lamindb Data Management (jaechang-hits/SciAgent-Skills, 370 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bulkrna Coexpression?

TianGzlab (a GitHub organization) maintains it in TianGzlab/OmicsClaw, which has 161 GitHub stars. The repository holds 88 skills in this directory. The repository was last updated on October 7, 2026.

Source: TianGzlab/OmicsClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.