nan-safe-correlation SKILL.md skillA

nan-safe-correlation from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add jaechang-hits/sciagent-skills/nan-safe-correlation@git:20260528.a0c28a2

Pins git:20260528.a0c28a2 in mdr.lock. Pin the fingerprint instead.

Audit grade
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Kind
SKILL.md skill
Repository
jaechang-hits/sciagent-skills
Path
skills/scientific-computing/nan-safe-correlation/SKILL.md
Versions recorded
1
Latest version
git:20260528.a0c28a2, committed May 28, 2026
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11,624 bytes
Repository stars
381
License
a license file GitHub does not identify

Per-feature NaN-safe Spearman/Pearson correlation across many features (genes, proteins, variants) with missing values. Covers why bulk matrix shortcuts fail, correct pairwise deletion, degenerate input filtering, and large-dataset performance. Use statistical-analysis for test choice; shap-model-explainability for interpretability.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# NaN-Safe Correlation Computation

## Overview

Computing correlations across many features (genes, proteins, variants) when missing values are present is error-prone. The most common mistake is using bulk matrix shortcuts that silently mishandle NaN, producing incorrect correlation values. This guide covers correct per-feature pairwise computation, degenerate input filtering, and performance optimization.

## Key Concepts

### Pairwise vs Listwise Deletion

- **Pairwise deletion**: For each feature pair, remove only samples where either value is NaN. Each feature uses the maximum available data.
- **Listwise deletion**: Remove any sample with NaN in any feature. Wastes valid data and biases results if missingness is not completely random.
- **Rule**: Always use pairwise deletion for per-feature correlations.

### Why Bulk Matrix Shortcuts Fail

Different features have different missing value patterns across samples. Bulk methods handle this inconsistently:

| Method | Problem |
|--------|---------|
| `DataFrame.rank()` then `corrwith()` | `rank()` assigns NaN ranks; `corrwith()` may drop globally or per-column inconsistently |
…

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How to install

The exact contents, by fingerprint
mdr add jaechang-hits/sciagent-skills/nan-safe-correlation@sha256:43c5c9cf10b1cb66

The line at the top of this page pins the label git:20260528.a0c28a2, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

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Versions

The registry has recorded 1 version of this file, committed on May 28, 2026.

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  • pass: Frontmatter declares a name
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  • pass: Size between 200 bytes and 200 KB (11624 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
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Source

GitHub

jaechang-hits/sciagent-skills · 381 stars · license a license file GitHub does not identify · pushed 2026-10-16 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_l7j723dx3xqzcoy5
GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/nan-safe-correlation
GET https://markdownregistry.com/api/v1/blob/43c5c9cf10b1cb664e1224933d68bc8c454acaec1f5484c950b80a127481f41e

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