PCAtools: everything Principal Components Analysis
Principal Component Analysis (PCA) extracts the fundamental structure of the data without the need to build any model to represent it. This "summary" of the data is arrived at through a process of reduction that can transform the large number of variables into a lesser number that are uncorrelated (i.e. the 'principal components'), while at the same time being capable of easy interpretation on the original data. PCAtools provides functions for data exploration via PCA, and allows the user to generate publication-ready figures. PCA is performed via BiocSingular; users can also identify an optimal number of principal components via different metrics, such as the elbow method and Horn's parallel analysis, which has relevance for data reduction in single-cell RNA-seq (scRNA-seq) and high dimensional mass cytometry data.
| System | Target | Derivation | Build status |
|---|---|---|---|
| x86_64-linux | /gnu/store/xf3sl970nx1inx12idlcbqb1wn3w6gmz-r-pcatools-2.2.0.drv | ||
| mips64el-linux | /gnu/store/dnj5d3nm7ck8zkg8y81i1bn22537pwb4-r-pcatools-2.2.0.drv | ||
| i686-linux | /gnu/store/6xc3afal0dav47q1p863qf7r9bf184h7-r-pcatools-2.2.0.drv | ||
| i586-gnu | /gnu/store/4nch0irkrq51z650hcw9pg0rh1g8jalv-r-pcatools-2.2.0.drv | ||
| armhf-linux | /gnu/store/rfafk15m4qm7b9qmrsgax8qx81fzc4gf-r-pcatools-2.2.0.drv | ||
| aarch64-linux | /gnu/store/gc9r8yvmij18brv0q7izd7nhq5v4w9sq-r-pcatools-2.2.0.drv |
| Linter | Message | Location |
|---|---|---|
| No lint warnings ✓ | ||