Scanpy Single-Cell Analysis
davila7/claude-code-templates
Walks through single-cell RNA-seq analysis with Scanpy: loading .h5ad and 10X data, QC, normalization, PCA and UMAP, Leiden clustering, marker genes and cell type annotation.
A skill your agent uses when identifying stable sample subtypes from bulk expression matrices with ConsensusClusterPlus, including PAC-based model selection and consensus matrix/CDF visualization.
Install Consensus Clustering Analysis
$ npx skills add aipoch/medical-research-skills --skill consensus-clustering-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aipoch/medical-research-skills consensus-clustering-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'awesome-med-research-skills/Data Analysis/consensus-clustering-analysis' .claude/skills/consensus-clustering-analysis && rm -rf skills-srcUse ~/.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/
Install the "consensus-clustering-analysis" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/consensus-clustering-analysis into .claude/skills/consensus-clustering-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consensus-clustering-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/consensus-clustering-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aipoch/medical-research-skills --skill consensus-clustering-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aipoch/medical-research-skills consensus-clustering-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/'awesome-med-research-skills/Data Analysis/consensus-clustering-analysis' .agents/skills/consensus-clustering-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "consensus-clustering-analysis" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/consensus-clustering-analysis into .agents/skills/consensus-clustering-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consensus-clustering-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aipoch/medical-research-skills --skill consensus-clustering-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aipoch/medical-research-skills consensus-clustering-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/'awesome-med-research-skills/Data Analysis/consensus-clustering-analysis' .cursor/skills/consensus-clustering-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "consensus-clustering-analysis" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/consensus-clustering-analysis into .cursor/skills/consensus-clustering-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consensus-clustering-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aipoch/medical-research-skills.git --path 'awesome-med-research-skills/Data Analysis/consensus-clustering-analysis'--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aipoch/medical-research-skills --skill consensus-clustering-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aipoch/medical-research-skills consensus-clustering-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/'awesome-med-research-skills/Data Analysis/consensus-clustering-analysis' .gemini/skills/consensus-clustering-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "consensus-clustering-analysis" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/consensus-clustering-analysis into .gemini/skills/consensus-clustering-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consensus-clustering-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aipoch/medical-research-skills consensus-clustering-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aipoch/medical-research-skills --skill consensus-clustering-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/'awesome-med-research-skills/Data Analysis/consensus-clustering-analysis' .github/skills/consensus-clustering-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "consensus-clustering-analysis" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/consensus-clustering-analysis into .github/skills/consensus-clustering-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consensus-clustering-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aipoch/medical-research-skills --skill consensus-clustering-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aipoch/medical-research-skills consensus-clustering-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/'awesome-med-research-skills/Data Analysis/consensus-clustering-analysis' .opencode/skills/consensus-clustering-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "consensus-clustering-analysis" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/consensus-clustering-analysis into .opencode/skills/consensus-clustering-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consensus-clustering-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
consensus-clustering-analysis- GitHub stars
- 2k
- Token cost
- ~2k tokens
- SKILL.md length
- 671 words
- Files
- 21 (incl. scripts, references)
- Skills in repo
- 567
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when identifying stable sample subtypes from bulk expression matrices with ConsensusClusterPlus, including PAC-based model selection and consensus matrix/CDF visualization.
- Works in 4 steps: Validate Input → Prepare Clustering Matrix → Run Consensus Clustering → …
- Identifying stable sample subtypes from bulk expression matrices with ConsensusClusterPlus
- SKILL.md covers When to Use, When to Read External Files, Usage and Arguments, plus 8 more sections
- Runs R scripts from its folder
What it does
Consensus Clustering Analysis is an agent skill from aipoch/medical-research-skills. Use when identifying stable sample subtypes from bulk expression matrices with ConsensusClusterPlus, including PAC-based model selection and consensus matrix/CDF visualization. NOT for: differential expression analysis, single-cell clustering workflows, or non-expression tables.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 24 other files, including scripts and reference files (for example `eval_report_consensus-clustering-analysis_result.json`, `references/algorithm.md` and `references/cli-guide.md`).
It sits in Research & Science, covering Bioinformatics. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.
When your agent uses it
- Identifying stable sample subtypes from bulk expression matrices with ConsensusClusterPlus
- Including PAC-based model selection and consensus matrix/CDF visualization
Example prompts
- “/consensus-clustering-analysis”
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 686e09d. 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 6 files in scripts/ (R, from the files we listed), which the agent can run.
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
Consensus Clustering Analysis loads about 2k tokens when it runs, and up to ~6.1k if it reads all its reference files. Until then it costs about 77 tokens; SKILL.md has 671 words of instructions outside code blocks.
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); the scripts in this folder are not scanned.
SKILL.md
The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 671 words, ~1,966 tokens.
Download SKILL.mdSave it as
.claude/skills/consensus-clustering-analysis/SKILL.md (or your agent's skills folder). This skill also uses 20 other files; get the full folder from GitHub.- name
- consensus-clustering-analysis
- description
- Use when identifying stable sample subtypes from bulk expression matrices with ConsensusClusterPlus, including PAC-based model selection and consensus matrix/CDF visualization. NOT for: differential expression analysis, single-cell clustering workflows, or non-expression tables.
- license
- MIT
- author
- AIPOCH
Consensus Clustering Analysis
When to Use
Use this skill when you need to identify stable sample subtypes from a bulk expression matrix with ConsensusClusterPlus, compare candidate clustering settings with PAC, and export consensus matrix/CDF visualizations.
Do not use this skill for differential expression analysis, single-cell clustering, or non-expression tabular data.
When to Read External Files
| Situation | File to Read | Purpose |
|---|---|---|
| Need algorithm details | references/algorithm.md | Consensus clustering, PAC scoring, and preprocessing assumptions |
| Need to run analysis | scripts/main.R | Execute: Rscript scripts/main.R --input_file ... --group_file ... |
| Encounter errors | references/troubleshooting.md | Common errors and solutions |
| Need CLI examples | references/cli-guide.md | Detailed CLI usage examples with verified local runs |
Usage
Rscript scripts/main.R \
--input_file ./expression_matrix.csv \
--group_file ./groups.csv \
--disease_group case \
--max_k 4 \
--output_dir ./output/ \
--gene_selection highly_variable \
--top_n 5000 \
--reps 1000 \
--p_item 0.8 \
--p_feature 1.0 \
--timeout_seconds 3600 \
--seed 42Arguments
| Short | Long | Type | Default | Description |
|---|---|---|---|---|
-i | --input_file | character | required | Expression matrix file (genes as rows, samples as columns) |
-g | --group_file | character | required | Group information file (sample ID + group columns) |
-d | --disease_group | character | case | Group label retained for clustering |
-k | --max_k | integer | 4 | Maximum cluster count to evaluate |
-o | --output_dir | character | ./output/ | Output directory |
-m | --gene_selection | character | highly_variable | Gene selection mode: highly_variable or custom |
-n | --top_n | integer | 5000 | Number of top variable genes to keep |
-l | --gene_list | character | NULL | Custom gene list file when gene_selection=custom |
-c | --center_data | logical | TRUE | Median-center each gene before clustering |
-r | --reps | integer | 1000 | Consensus resampling repetitions |
--p_item | double | 0.8 | Sample resampling proportion | |
--p_feature | double | 1.0 | Feature resampling proportion | |
-t | --timeout_seconds | integer | 3600 | Elapsed timeout in seconds |
-s | --seed | integer | 42 | Random seed for reproducibility |
Input Format
Expression Matrix (input_file)
Genes as rows, samples as columns, CSV/TSV/TXT format with gene ID in the first column.
,Sample01,Sample02,Sample03
TSPAN6,1.8479,1.8318,3.8276
TNMD,0.0349,0.0533,1.3889Group File (group_file)
Delimited text file with sample ID and group columns.
sample,group
Sample01,case
Sample02,control
Sample03,caseGene List (gene_list)
Optional plain text or single-column CSV file with one gene symbol per line.
TNMD
DPM1
SCYL3Output Files
| File | Description |
|---|---|
Cluster_res.csv | PAC summary for each distance/algorithm combination with is_best marking the selected model |
genes_for_clustering.csv | Selected genes and gene selection mode |
samples_for_clustering.csv | Samples retained after disease-group filtering |
result_<distance>_<algorithm>/ | Method-specific consensus outputs and PAC_scores.csv |
Consensus Matrix Plot.pdf | Consensus matrix heatmap for the optimal model |
CDF curve Plot.pdf | CDF curves for the optimal method |
session_info.txt | R session and package version info |
Workflow
Step 1: Validate Input
- Check file existence
- Detect sample and group columns in the group file
- Validate sample matching between expression matrix and group file
Step 2: Prepare Clustering Matrix
- Filter samples by the requested disease group
- Select genes using
highly_variableorcustom - Median-center genes if requested
Show full SKILL.md (281 more words)Show less
Step 3: Run Consensus Clustering
- Evaluate supported distance and clustering algorithm combinations
- Compute PAC scores across candidate K values
- Select the optimal model by minimum PAC
Step 4: Generate Outputs
- Save result tables
- Generate consensus matrix and CDF plots
- Record session information for reproducibility
Methods
ConsensusClusterPlus
Repeated subsampling is used to estimate cluster stability across candidate K values and clustering settings.
PAC Score
The proportion of ambiguous clustering is computed as CDF(0.9) - CDF(0.1) from lower-triangle consensus values. Lower PAC indicates more stable clustering.
Gene Selection
highly_variable: rank genes by median absolute deviationcustom: use the intersection of the provided gene list and matrix row names
Examples
Basic Usage
Rscript scripts/main.R \
-i expression_matrix.csv \
-g groups.csv \
-d case \
-k 3 \
-r 20 \
-o output/example_basic \
-t 120With a Custom Gene List
Rscript scripts/main.R \
-i expression_matrix.csv \
-g groups.csv \
-d case \
-m custom \
-l genes.csv \
-k 4 \
-r 20 \
-o output/example_custom \
-t 120Without Median Centering
Rscript scripts/main.R \
-i expression_matrix.csv \
-g groups.csv \
-d case \
-c FALSE \
-k 3 \
-r 20 \
-o output/example_rawscale \
-t 120Error Handling
Common Errors
| Error | Cause | Solution |
|---|---|---|
SKILL_FILE_NOT_FOUND | Input file does not exist | Check file path and permissions |
SKILL_MISSING_COLUMNS | Group file lacks sample/group columns | Verify column names in the group file |
SKILL_SAMPLE_MISMATCH | Sample names do not match | Ensure group file sample IDs match matrix columns |
SKILL_INVALID_PARAMETER | CLI value is invalid | Check allowed options and numeric ranges |
SKILL_INVALID_DATA | Too few samples/genes remain after filtering | Lower max_k or review the input data |
SKILL_TIMEOUT | Run exceeded the configured timeout | Increase timeout_seconds or reduce reps |
SKILL_DEPENDENCY_MISSING | Required R package is not installed | Install missing packages before rerunning |
IF error persists, READ: references/troubleshooting.md
Testing
Smoke Check
# Check help
Rscript scripts/main.R --help
# Run analysis
Rscript scripts/main.R \
-i tests/data/expression_matrix.csv \
-g tests/data/groups.csv \
-d case \
-k 3 \
-r 20 \
-o output/example_basic \
-t 120Validation Commands
# Inspect selected model
cat output/example_basic/Cluster_res.csv
# Check output plots exist
ls -la output/example_basicImplementation Checklist
- CLI parsing with
optparse -
set.seed()for reproducibility -
requireNamespace()dependency checks - Session info recording
-
data.table::fread()input reading - File reading instructions in
SKILL.md - Modular script structure (<150 lines per file)
- Test data provided
- Error handling with
SKILL_*codes - Scripts in
scripts/directory - References in
references/directory
Last updated: 2026-04-17 | Version: 1.0.0
© aipoch, MIT. 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 20 other files (scripts, references) in awesome-med-research-skills/Data Analysis/consensus-clustering-analysis of aipoch/medical-research-skills.
- SKILL.md
- DESCRIPTION
- eval_report_consensus-clustering-analysis_result.json
- references/algorithm.md
- references/cli-guide.md
- references/troubleshooting.md
- scripts/functions_analysis.R
- scripts/io_utils.R
- scripts/main.R
- scripts/run_analysis.R
- scripts/utils.R
- scripts/visualization.R
- tests/data/expression_matrix.csv
- tests/data/genes.csv
- tests/data/groups.csv
- tests/run_tests.R
- tests/testthat.R
- … and 4 more
Open the folder on GitHubat commit 686e09d
Compare with similar skills
Consensus Clustering Analysis 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Consensus Clustering Analysis this skillaipoch/medical-research-skills | 2k | — | ~2k | Automated safety check: Pass | MIT | |
| Scanpy Single-Cell Analysisdavila7/claude-code-templates | 32k | 16 repos | ~2.8k | Automated safety check: Pass | MIT | |
| deepTools NGS Toolkitdavila7/claude-code-templates | 32k | 13 repos | ~4.5k | Automated safety check: Pass | MIT | |
| PyDESeq2 Differential Expressiondavila7/claude-code-templates | 32k | 12 repos | ~4k | Automated safety check: Pass | MIT | |
| Gtars Genomic Interval Toolkitdavila7/claude-code-templates | 32k | 12 repos | ~1.9k | Automated safety check: Pass | MIT | |
| LaminDB Biological Data Managementdavila7/claude-code-templates | 32k | 12 repos | ~3.6k | Automated safety check: Pass | MIT |
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PyDESeq2 Differential Expression
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Runs differential gene expression analysis on bulk RNA-seq counts with PyDESeq2: design formulas, Wald tests, FDR correction and volcano or MA plots.
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Single-Cell Initial Analysis
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Related
Categories
Questions about Consensus Clustering Analysis
What does Consensus Clustering Analysis do?
A skill your agent uses when identifying stable sample subtypes from bulk expression matrices with ConsensusClusterPlus, including PAC-based model selection and consensus matrix/CDF visualization. Consensus Clustering Analysis is an agent skill from aipoch/medical-research-skills. Use when identifying stable sample subtypes from bulk expression matrices with ConsensusClusterPlus, including PAC-based model selection and consensus matrix/CDF visualization.
When should I use Consensus Clustering Analysis?
Consensus Clustering Analysis fits situations like: identifying stable sample subtypes from bulk expression matrices with ConsensusClusterPlus; including PAC-based model selection and consensus matrix/CDF visualization.
How do I install Consensus Clustering Analysis in Claude Code?
Run `npx skills add aipoch/medical-research-skills --skill consensus-clustering-analysis -a claude-code`. Or copy the skill folder (awesome-med-research-skills/Data Analysis/consensus-clustering-analysis in aipoch/medical-research-skills) into .claude/skills/consensus-clustering-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Consensus Clustering Analysis in Codex?
Run `npx skills add aipoch/medical-research-skills --skill consensus-clustering-analysis -a codex`. Or copy the skill folder (awesome-med-research-skills/Data Analysis/consensus-clustering-analysis in aipoch/medical-research-skills) into .agents/skills/consensus-clustering-analysis in your project. Codex loads it when a task matches its description.
Can I use Consensus Clustering Analysis 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 aipoch/medical-research-skills --skill consensus-clustering-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/consensus-clustering-analysis, .gemini/skills/consensus-clustering-analysis, .github/skills/consensus-clustering-analysis and .opencode/skills/consensus-clustering-analysis in your project.
What does Consensus Clustering Analysis need to run?
Going by SKILL.md and its folder, Consensus Clustering Analysis needs R for the scripts in its folder.
Does Consensus Clustering Analysis 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 Consensus Clustering Analysis 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Consensus Clustering Analysis use?
Consensus Clustering Analysis is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Consensus Clustering Analysis use?
About 2k tokens (SKILL.md is roughly 7.9k 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 4.1k tokens, read only when the agent opens those files.
What are the alternatives to Consensus Clustering Analysis?
Skills that share tags, products or a category with Consensus Clustering Analysis: Scanpy Single-Cell Analysis (davila7/claude-code-templates, 32k stars), deepTools NGS Toolkit (davila7/claude-code-templates, 32k stars), PyDESeq2 Differential Expression (davila7/claude-code-templates, 32k stars) and Gtars Genomic Interval Toolkit (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Consensus Clustering Analysis?
aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,973 GitHub stars. The repository holds 567 skills in this directory. The repository was last updated on September 17, 2026.
Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.