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pPCA

Partial Principal Component Analysis of Partitioned Large Sparse Matrices

v1.1 · Oct 21, 2024 · GPL-3

Description

Performs partial principal component analysis of a large sparse matrix. The matrix may be stored as a list of matrices to be concatenated (implicitly) horizontally. Useful application includes cases where the number of total nonzero entries exceed the capacity of 32 bit integers (e.g., with large Single Nucleotide Polymorphism data).

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r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
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r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK
Check details (14 non-OK)
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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Dependency Network

Dependencies Reverse dependencies RSpectra Matrix Rcpp pPCA

Version History

new 1.1 Mar 9, 2026