slideimp: Numeric Matrices K-NN and PCA Imputation

Fast k-nearest neighbors (K-NN) and principal component analysis (PCA) imputation algorithms for missing values in epigenetic data or other high-dimensional numeric matrices. For PCA, a locally optimal block preconditioned conjugate gradient (LOBPCG) eigensolver with warm starts of both the eigenblock and search direction is also supported. Two complementary imputation strategies are available. Group-wise imputation (e.g., by chromosome) is recommended for Illumina DNA methylation microarrays (e.g., 450K, EPIC) and other matrices with groupable columns. A sliding window approach for K-NN or PCA imputation is recommended only for whole-genome methylation data such as whole-genome bisulfite sequencing (WGBS) or Enzymatic Methyl-seq (EM-seq). The package also supports hyperparameter tuning via repeated cross-validation. The K-NN algorithm is described in: Hastie, T., Tibshirani, R., Sherlock, G., Eisen, M., Brown, P. and Botstein, D. (1999) "Imputing Missing Data for Gene Expression Arrays". The PCA imputation is an optimized reimplementation of the imputePCA() function from the 'missMDA' package described in: Josse, J. and Husson, F. (2016) <doi:10.18637/jss.v070.i01> "missMDA: A Package for Handling Missing Values in Multivariate Data Analysis".

Version:	1.2.0
Depends:	R (≥ 4.3.0)
Imports:	bigmemory, checkmate, cli, collapse, mirai, Rcpp, stats, utils
LinkingTo:	Rcpp, RcppArmadillo, RcppThread
Suggests:	knitr, missMDA, RhpcBLASctl, rmarkdown, testthat (≥ 3.0.0), withr
Published:	2026-06-16
DOI:	10.32614/CRAN.package.slideimp
Author:	Hung Pham [aut, cre, cph], Posit Software, PBC [cph] (Copyright holder of code adapted from the 'carrier' package, MIT licensed)
Maintainer:	Hung Pham <amser.hoanghung at gmail.com>
BugReports:	https://github.com/hhp94/slideimp/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://github.com/hhp94/slideimp, https://hhp94.github.io/slideimp/
NeedsCompilation:	yes
Language:	en-US
Citation:	slideimp citation info
Materials:	README, NEWS
CRAN checks:	slideimp results

Documentation:

Reference manual:	slideimp.html , slideimp.pdf
Vignettes:	slideimp (source, R code)

Downloads:

Package source:	slideimp_1.2.0.tar.gz
Windows binaries:	r-devel: slideimp_1.2.0.zip, r-release: slideimp_1.2.0.zip, r-oldrel: slideimp_1.2.0.zip
macOS binaries:	r-release (arm64): slideimp_1.2.0.tgz, r-oldrel (arm64): slideimp_1.2.0.tgz, r-release (x86_64): slideimp_1.2.0.tgz, r-oldrel (x86_64): slideimp_1.2.0.tgz
Old sources:	slideimp archive

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