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Orthogonal Sparse Non-Negative Matrix Tri-Factorization

0packages depend
2.1Kdownloads / year
test coverage
11/13checks pass

Overview

About
Maintained by Xiaoyao YinFirst published 2019-11-281 releasesCRAN page ↗

A novel method to implement cancer subtyping and subtype specific drug targets identification via non-negative matrix tri-factorization. To improve the interpretability, we introduce orthogonal constraint to the row coefficient matrix and column coefficient matrix. To meet the prior knowledge that each subtype should be strongly associated with few gene sets, we introduce sparsity constraint to the association sub-matrix. The average residue was introduced to evaluate the row and column cluster numbers. This is part of the work "Liver Cancer Analysis via Orthogonal Sparse Non-Negative Matrix Tri- Factorization" which will be submitted to BBRC.

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CRAN checks
2NOTE11OK
Failing flavors
  • NOTE r-devel-linux-x86_64-debian-clang
  • NOTE r-devel-linux-x86_64-debian-gcc
Slowest check: 1.4 min · r-oldrel-windows-x86_64
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Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
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Dependencies · direct
Check history
  • NOTE2026-03-10
    9 OK · 5 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
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Documented parameters
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Return-value docs
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References docs
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Dependencies

Declared dependencies
3 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.4.4
Imports (3)
dplyrMASSstats
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none
Suggests (2)
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Listed in earlier versions (1)
no longer listed · 0.1.0
Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.0Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2019-11-28
Total releases
1 / 7 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 3.4.4
Download size
322 KB
Installed size
not tracked yet
With dependencies
not tracked yet
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