impute_bpca: Impute missing values using Bayesian PCA

In metamorphr: Tidy and Streamlined Metabolomics Data Workflows

Impute missing values using Bayesian PCA

Description

One of several PCA-based imputation methods. Basically a wrapper around ⁠pcaMethods::⁠pca(method = "bpca"). For a detailed discussion, see the vignette("pcaMethods") and vignette("missingValues", "pcaMethods") as well as the References section.

Important Note

impute_bpca() depends on the pcaMethods package from Bioconductor. If metamorphr was installed via install.packages(), dependencies from Bioconductor were not automatically installed. When impute_bpca() is called without the pcaMethods package installed, you should be asked if you want to install pak and pcaMethods. If you want to use impute_bpca() you have to install those. In case you run into trouble with the automatic installation, please install pcaMethods manually. See pcaMethods – a Bioconductor package providing PCA methods for incomplete data.

Usage

impute_bpca(data, n_pcs = 2, center = TRUE, scale = "none", direction = 2)

Arguments

data	A tidy tibble created by read_featuretable.
n_pcs	The number of PCs to calculate.
center	Should data be mean centered? See prep for details.
scale	Should data be scaled? See prep for details.
direction	Either 1 or 2. 1 runs a PCA on a matrix with samples in columns and features in rows and 2 runs a PCA on a matrix with features in columns and samples in rows. Both are valid according to this discussion on GitHub but give different results.

Value

A tibble with imputed missing values.

References

• H. R. Wolfram Stacklies, 2017, DOI 10.18129/B9.BIOC.PCAMETHODS.

• W. Stacklies, H. Redestig, M. Scholz, D. Walther, J. Selbig, Bioinformatics 2007, 23, 1164–1167, DOI 10.1093/bioinformatics/btm069.

Examples

toy_metaboscape %>%
  impute_bpca()

metamorphr documentation built on June 10, 2026, 5:07 p.m.