Bio Outlier Splicing Detection
GPTomics/bioSkills
Detects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q…
A skill your agent uses when filtering genes with high missingness and then imputing missing values in a bulk expression matrix with group-aware KNN through DMwR2, where donor samples are restricted…
Install Knn Imputation
$ npx skills add aipoch/medical-research-skills --skill knn-imputation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aipoch/medical-research-skills knn-imputation --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/knn-imputation' .claude/skills/knn-imputation && 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 "knn-imputation" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/knn-imputation into .claude/skills/knn-imputation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knn-imputation", 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/knn-imputationType 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 knn-imputation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aipoch/medical-research-skills knn-imputation --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/knn-imputation' .agents/skills/knn-imputation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "knn-imputation" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/knn-imputation into .agents/skills/knn-imputation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knn-imputation", 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 knn-imputation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aipoch/medical-research-skills knn-imputation --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/knn-imputation' .cursor/skills/knn-imputation && 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 "knn-imputation" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/knn-imputation into .cursor/skills/knn-imputation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knn-imputation", 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/knn-imputation'--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 knn-imputation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aipoch/medical-research-skills knn-imputation --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/knn-imputation' .gemini/skills/knn-imputation && 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 "knn-imputation" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/knn-imputation into .gemini/skills/knn-imputation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knn-imputation", 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 knn-imputationInstalls 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 knn-imputation -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/knn-imputation' .github/skills/knn-imputation && 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 "knn-imputation" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/knn-imputation into .github/skills/knn-imputation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knn-imputation", 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 knn-imputation -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 knn-imputation --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/knn-imputation' .opencode/skills/knn-imputation && 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 "knn-imputation" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/knn-imputation into .opencode/skills/knn-imputation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knn-imputation", 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
knn-imputation- GitHub stars
- 2k
- Token cost
- ~2.5k tokens
- SKILL.md length
- 976 words
- Files
- 14 (incl. scripts, references)
- Skills in repo
- 578
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when filtering genes with high missingness and then imputing missing values in a bulk expression matrix with group-aware KNN through DMwR2, where donor samples are restricted…
- Works in 5 steps: Validate Input → Filter Genes → Build Strata → …
- Filtering genes with high missingness and then imputing missing values in a bulk expression matrix with group-aware KNN through DMwR2
- SKILL.md covers When to Use, When to Read External Files, Input Validation and Prerequisites, plus 10 more sections
- Runs R scripts from its folder
What it does
Knn Imputation is an agent skill from aipoch/medical-research-skills. Use when filtering genes with high missingness and then imputing missing values in a bulk expression matrix with group-aware KNN through DMwR2, where donor samples are restricted by one annotation column before imputation. For strata with 10 or fewer samples, the script falls back to row-wise direct filling with mean or median. NOT for: single-cell data, multi-column stratification, non-tabular inputs, network access, or interactive workflows.
Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 17 other files, including scripts and reference files (for example `eval_report_knn-imputation_result.json`, `references/algorithm.md` and `references/cli-guide.md`).
It sits in Research & Science, covering Bioinformatics and Data cleaning. 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
- Filtering genes with high missingness and then imputing missing values in a bulk expression matrix with group-aware KNN through DMwR2
- Where donor samples are restricted by one annotation column before imputation
Example prompts
- “/knn-imputation”
Workflow steps
5 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), 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
Knn Imputation loads about 2.5k tokens when it runs, and up to ~5.2k if it reads all its reference files. Until then it costs about 116 tokens; SKILL.md has 976 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). 976 words, ~2,494 tokens.
Download SKILL.mdSave it as
.claude/skills/knn-imputation/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.- name
- knn-imputation
- description
- Use when filtering genes with high missingness and then imputing missing values in a bulk expression matrix with group-aware KNN through DMwR2, where donor samples are restricted by one annotation column before imputation. For strata with 10 or fewer samples, the script falls back to row-wise direct filling with mean or median. NOT for: single-cell data, multi-column stratification, non-tabular inputs, network access, or interactive workflows.
- license
- MIT
- skill-author
- AIPOCH
KNN Imputation
When to Use
Use this skill when you need to remove genes with more than 50% missing values from a bulk expression matrix and then run group-aware KNN imputation, with the donor pool restricted by one grouping column.
Do not use this skill for:
- single-cell data
- multi-column stratification
- non-tabular inputs
- network-dependent workflows
- interactive analysis sessions
When to Read External Files
| Situation | File to Read | Purpose |
|---|---|---|
| Need algorithm details | references/algorithm.md | Group-stratified KNN method, fallback rules, and 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 |
| Need sample input fixtures | tests/data/ | Repository fixtures for local validation and examples |
Input Validation
This skill accepts: a bulk expression matrix CSV (features × samples) and a sample annotation CSV file with a single grouping column for KNN stratification.
If the user's request does not involve imputing missing values in a bulk expression matrix — for example, asking to impute single-cell data, use multi-column stratification, or run network-dependent workflows — do not proceed with the workflow. Instead respond:
"knn-imputation is designed to filter and impute missing values in bulk expression matrices using group-aware KNN with DMwR2. Your request appears to be outside this scope. Please provide a bulk expression matrix with a single grouping column, or use a more appropriate tool for your task."
Prerequisites
DMwR2 is not available on CRAN. Install it from GitHub before running:
install.packages("remotes")
remotes::install_github("cran/DMwR2")If SKILL_DEPENDENCY_MISSING is raised, use the command above to install DMwR2 before retrying. Standard install.packages("DMwR2") will not work.
Usage
Rscript scripts/main.R \
--input_file tests/data/sample_expression_matrix.csv \
--group_file tests/data/sample_groups.csv \
--output_dir tests/output/basic_run \
--sample_column sample \
--group_column group \
--k 10 \
--small_strata_fill_method mean \
--overwrite \
--timeout_seconds 0 \
--seed 42If re-running into an existing output_dir, pass --overwrite. Otherwise use a fresh output directory.
Arguments
| Short | Long | Type | Default | Description |
|---|---|---|---|---|
-i | --input_file | character | required | Expression matrix CSV file with features in rows and samples in columns |
-g | --group_file | character | required | Sample annotation CSV file |
-o | --output_dir | character | ./output/ | Output directory |
-c | --sample_column | character | sample | Sample ID column in the group file |
-l | --group_column | character | group | Single grouping column used to define imputation strata |
-k | --k | integer | 10 | Number of nearest neighbors used inside each stratum |
-m | --small_strata_fill_method | character | mean | Fill method for strata with 10 or fewer samples: mean or median |
--overwrite | flag | FALSE | Overwrite existing output files in output_dir | |
-t | --timeout_seconds | integer | 0 | Optional elapsed timeout in seconds, 0 disables timeout |
-s | --seed | integer | 42 | Random seed for reproducibility |
Input Format
Expression Matrix (input_file)
Features as rows, samples as columns, CSV format with feature ID in the first column.
,Sample01,Sample02,Sample03
TSPAN6,1.84,1.83,3.82
SEMA3F,4.83,4.04,5.28Requirements:
- The first column stores feature IDs.
- All remaining columns must be numeric or empty.
- Missing values must be encoded as empty cells or
NA.
Group File (group_file)
CSV with one sample ID column and one grouping column.
sample,group
Sample01,case
Sample02,control
Sample03,caseRequirements:
sample_columnmust match the expression matrix sample names exactly.- The column named in
group_columnmust exist in the group file. sample_columnand the selected grouping column must be non-missing.- KNN only runs for strata with at least 11 samples.
- Strata with 10 or fewer samples use row-wise direct filling with
--small_strata_fill_method.
Output Files
| File | Format | Description |
|---|---|---|
imputed_expression_matrix.csv | CSV | Complete imputed expression matrix |
session_info.txt | TXT | R session and package version information |
Workflow
Step 1: Validate Input
- Check file existence.
- Validate sample matching between expression matrix and group file.
- Verify that the requested grouping column exists.
Step 2: Filter Genes
- Remove genes whose missing-value fraction across all samples is at least 50%.
- Stop if all genes are removed by this filter.
Step 3: Build Strata
- Construct one stratum per unique value in
group_column. - Keep strata even when they are small; only strata with at least 11 samples run KNN.
Show full SKILL.md (384 more words)Show less
Step 4: Run Imputation
- Run group-stratified KNN imputation only within strata that contain at least 11 samples.
- Within each stratum, skip imputation for any gene whose missing-value fraction in that stratum is at least 50%; leave those values as
NA. - For strata with 10 or fewer samples, fill missing values by the row-wise mean or median within that stratum.
- If a small stratum has an all-missing gene row that is still imputable, fall back to the global row-wise mean or median.
Step 5: Save Results
- Write the imputed matrix.
- Save
session_info.txtto the output directory.
Methods
Missingness Filter + Group-Stratified DMwR2 KNN
Genes with at least 50% missing values are removed first. KNN imputation is then applied within user-defined strata built from one grouping column when the stratum contains at least 11 samples.
If the chosen grouping scheme splits the data into strata of 10 samples or fewer, the command falls back to row-wise direct filling by mean or median inside that stratum. Genes that reach at least 50% missingness within a stratum are skipped in that stratum and remain NA. If another small-stratum row is fully missing but still below that threshold, the script falls back to the corresponding global row summary.
For implementation details, assumptions, and skip behavior for small strata, read references/algorithm.md.
Examples
Basic Usage
Rscript scripts/main.R \
-i tests/data/sample_expression_matrix.csv \
-g tests/data/sample_groups.csv \
-o tests/output/basic_runSmaller Neighborhood
Rscript scripts/main.R \
-i tests/data/sample_expression_matrix.csv \
-g tests/data/sample_groups.csv \
-o tests/output/k5_run \
-k 5Small Strata Fallback
Rscript scripts/main.R \
-i tests/data/sample_expression_matrix.csv \
-g tests/data/sample_groups.csv \
-o tests/output/small_strata_run \
-l sample \
-m median \
--overwriteError Handling
Common Errors
| Error | Cause | Solution |
|---|---|---|
SKILL_FILE_NOT_FOUND | Input file does not exist | Check the file path |
SKILL_EMPTY_FILE | Input file exists but is empty | Replace it with a valid non-empty CSV file |
SKILL_OUTPUT_EXISTS | Output files already exist | Re-run with --overwrite or change --output_dir |
SKILL_SAMPLE_MISMATCH | Sample names do not match between files | Verify exact sample name matching |
SKILL_MISSING_COLUMNS | Requested grouping column is absent | Add that column to the group file or change --group_column |
SKILL_INVALID_PARAMETER | Multiple grouping columns were supplied | Pass exactly one grouping column in --group_column |
SKILL_INVALID_DATA | Matrix or group file structure is invalid | Check input format, duplicated IDs, and group completeness |
SKILL_DEPENDENCY_MISSING | DMwR2 not installed | Install with: Rscript -e "install.packages('remotes'); remotes::install_github('cran/DMwR2')" — note: DMwR2 is not on CRAN |
SKILL_TIMEOUT | Timeout limit was exceeded | Increase --timeout_seconds or reduce data size |
IF error persists, READ: references/troubleshooting.md
Local Validation
Validate the CLI Entrypoint
# Check help
Rscript scripts/main.R --help
# Run with sample data
Rscript scripts/main.R \
-i tests/data/sample_expression_matrix.csv \
-g tests/data/sample_groups.csv \
-o tests/output/basic_run \
--overwrite
# Run forced small-strata fallback
Rscript scripts/main.R \
-i tests/data/sample_expression_matrix.csv \
-g tests/data/sample_groups.csv \
-o tests/output/small_strata_run \
-l sample \
-m median \
--overwriteOutput Checks
# Count lines in output
wc -l tests/output/basic_run/imputed_expression_matrix.csv
# Check output files exist
ls -la tests/output/basic_runReference Files
| File | Purpose |
|---|---|
references/algorithm.md | Group-stratified KNN method, fallback rules, and assumptions |
references/troubleshooting.md | Common errors and solutions |
references/cli-guide.md | CLI usage examples |
© 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 13 other files (scripts, references) in awesome-med-research-skills/Data Analysis/knn-imputation of aipoch/medical-research-skills.
- SKILL.md
- eval_report_knn-imputation_result.json
- references/algorithm.md
- references/cli-guide.md
- references/troubleshooting.md
- scripts/functions.R
- scripts/imputation_functions.R
- scripts/imputation_helpers.R
- scripts/main.R
- scripts/run_analysis.R
- scripts/utils.R
- tests/data/sample_expression_matrix.csv
- tests/data/sample_groups.csv
- tests/data/sample_groups_custom.csv
Open the folder on GitHubat commit 686e09d
Compare with similar skills
Knn Imputation 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 |
|---|---|---|---|---|---|---|
| Knn Imputation this skillaipoch/medical-research-skills | 2k | — | ~2.5k | Automated safety check: Pass | MIT | |
| Bio Outlier Splicing DetectionGPTomics/bioSkills | 1.2k | 2 repos | ~5.1k | Automated safety check: Pass | MIT | |
| Bio Proteomics Data ImportFreedomIntelligence/OpenClaw-Medical-Skills | 3.1k | 1 repos | ~1.2k | Automated safety check: Pass | None | |
| Rare Disease RnaseqClawBio/ClawBio | 1.2k | 1 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Bio Splicing QcGPTomics/bioSkills | 1.2k | 2 repos | ~6.2k | Automated safety check: Pass | MIT | |
| Bio Proteomics Proteomics QcFreedomIntelligence/OpenClaw-Medical-Skills | 3.1k | 1 repos | ~1.8k | Automated safety check: Pass | None |
Similar skills
Bio Proteomics Data Import
FreedomIntelligence/OpenClaw-Medical-Skills
Load and parse mass spectrometry data formats including mzML, mzXML, and quantification tool outputs like MaxQuant proteinGroups.txt.
Rare Disease Rnaseq
ClawBio/ClawBio
Blood RNA-seq expression-outlier detection for rare-disease diagnostics.
Bio Splicing Qc
GPTomics/bioSkills
Assesses RNA-seq data quality specifically for alternative splicing analysis.
Bio Proteomics Proteomics Qc
FreedomIntelligence/OpenClaw-Medical-Skills
Quality control and assessment for proteomics data. An agent skill from FreedomIntelligence/OpenClaw-Medical-Skills.
Bio Workflows Methylation Pipeline
GPTomics/bioSkills
Orchestrates the end-to-end bisulfite/EM-seq methylation pipeline from FASTQ to differentially methylated regions, chaining Trim Galore/fastp QC, Bismark alignment + deduplication, methylation…
More from aipoch/medical-research-skills
All 578 skills in this repoAcademic Poster Generator
aipoch/medical-research-skills
Complete workflow for generating academic research posters from PDF literature; use when you need to extract paper content from PDFs and produce a LaTeX-based poster…
Diagnostic Study Quality Assessment Quadas
aipoch/medical-research-skills
Analyzes clinical diagnostic accuracy studies for bias using the QUADAS-2 tool.
Exploratory Data Analysis
aipoch/medical-research-skills
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats.
Iso Certification
aipoch/medical-research-skills
A toolkit for preparing ISO 13485:2016 certification documentation for medical device QMS.
Journal Skills
aipoch/medical-research-skills
Recommends target journals for manuscript submission by analyzing the paper topic/abstract and the journal distribution of similar PubMed literature; use when users ask for journal…
Latex Posters
aipoch/medical-research-skills
Creates academic-poster writing packages for LaTeX using beamerposter, tikzposter, or baposter.
Related
Categories
Questions about Knn Imputation
What does Knn Imputation do?
A skill your agent uses when filtering genes with high missingness and then imputing missing values in a bulk expression matrix with group-aware KNN through DMwR2, where donor samples are restricted…. Knn Imputation is an agent skill from aipoch/medical-research-skills. Use when filtering genes with high missingness and then imputing missing values in a bulk expression matrix with group-aware KNN through DMwR2, where donor samples are restricted by one annotation column before imputation.
When should I use Knn Imputation?
Knn Imputation fits situations like: filtering genes with high missingness and then imputing missing values in a bulk expression matrix with group-aware KNN through DMwR2; where donor samples are restricted by one annotation column before imputation.
How do I install Knn Imputation in Claude Code?
Run `npx skills add aipoch/medical-research-skills --skill knn-imputation -a claude-code`. Or copy the skill folder (awesome-med-research-skills/Data Analysis/knn-imputation in aipoch/medical-research-skills) into .claude/skills/knn-imputation in your project. Claude Code loads it when a task matches its description.
How do I install Knn Imputation in Codex?
Run `npx skills add aipoch/medical-research-skills --skill knn-imputation -a codex`. Or copy the skill folder (awesome-med-research-skills/Data Analysis/knn-imputation in aipoch/medical-research-skills) into .agents/skills/knn-imputation in your project. Codex loads it when a task matches its description.
Can I use Knn Imputation 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 knn-imputation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/knn-imputation, .gemini/skills/knn-imputation, .github/skills/knn-imputation and .opencode/skills/knn-imputation in your project.
What does Knn Imputation need to run?
Going by SKILL.md and its folder, Knn Imputation needs R for the scripts in its folder.
Does Knn Imputation 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 Knn Imputation 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 Knn Imputation use?
Knn Imputation 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 Knn Imputation use?
About 2.5k tokens (SKILL.md is roughly 10k 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 2.7k tokens, read only when the agent opens those files.
What are the alternatives to Knn Imputation?
Skills that share tags, products or a category with Knn Imputation: Bio Outlier Splicing Detection (GPTomics/bioSkills, 1.2k stars), Bio Proteomics Data Import (FreedomIntelligence/OpenClaw-Medical-Skills, 3.1k stars), Rare Disease Rnaseq (ClawBio/ClawBio, 1.2k stars) and Bio Splicing Qc (GPTomics/bioSkills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Knn Imputation?
aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,978 GitHub stars. The repository holds 578 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.