# pca-plot

> The 'pca-plot' package is a way to check seq data quality. It visualises the data conditionally in a 2D or 3D plot (dependent on the number of PCs selected), where each point represents a sample. The distance between the points is a measure of the similar

Latest version **1.0.4** (published 2023-12-10) · 0 weekly downloads

## Install

```sh
npm install pca-plot
pnpm add pca-plot
yarn add pca-plot
bun add pca-plot
```

## Health

**Score 20/100 (F)** — status: abandoned.

Positive: esm support; no vulnerabilities.

Warnings: low downloads; no types.

Negative: abandoned; low maintenance score.

## Facts

| | |
|---|---|
| Version | 1.0.4 |
| Published | 2023-12-10 |
| First published | 2023-11-25 |
| Weekly downloads | 0 |
| TypeScript types | none |
| Module format | ESM + CommonJS |
| Dependencies | 6 |
| Unpacked size | 3.3 MB |
| Known vulnerabilities | 0 |
| Install scripts | no |
| Author | cedekpoole |
| Maintainers | cedekpoole |
| Keywords | react, highcharts, data-visualization, pca, genomics |

## Links

- npm: https://www.npmjs.com/package/pca-plot
- Repository: https://github.com/cedekpoole/PCA-plot
- Homepage: https://github.com/cedekpoole/PCA-plot#readme
- Issues: https://github.com/cedekpoole/PCA-plot/issues
- npm.io page: https://npm.io/package/pca-plot

## Dependencies (6)

- [ml-pca](https://npm.io/package/ml-pca.md) ^4.1.1
- [papaparse](https://npm.io/package/papaparse.md) ^5.4.1
- [file-saver](https://npm.io/package/file-saver.md) ^2.0.5
- [highcharts](https://npm.io/package/highcharts.md) ^11.1.0
- [@blueprintjs/core](https://npm.io/package/@blueprintjs/core.md) ^5.7.1
- [highcharts-react-official](https://npm.io/package/highcharts-react-official.md) ^3.2.1

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## Recent versions

- 1.0.4 (latest) — 2023-12-10
- 1.0.3 — 2023-11-29
- 1.0.2 — 2023-11-29
- 1.0.1 — 2023-11-26
- 1.0.0 — 2023-11-25

## README

# Principal Component Analysis (PCA) plot 

The 'pca-plot' package is a way to check seq data quality. It visualises the data conditionally in a 2D or 3D plot (dependent on the number of PCs selected), where each point represents a sample. The distance between the points is a measure of the similarity between the samples. The more similar the samples are, the closer the points will be to each other. 

## Installation

```bash
npm install pca-plot
```

## Usage

```javascript
import { PCAPlot } from 'pca-plot';

const App = () => {
    return (
        <>
        <PCAPlot />
        </>
    )
}

export default App;
```

---
_Source: https://npm.io/package/pca-plot · Machine-readable twin of the npm.io package page. Health data is recomputed on every publish._