Supervised NMF
Overview
Non-negative Matrix Factorization(NMF) is a powerful tool for identifying the key features of microbial communities and a dimension-reduction method. When we are interested in the differences between the structures of two groups of communities, supervised NMF(Yun Cai, Hong Gu and Tobby Kenney (2017),doi:10.1186/s40168-017-0323-1) provides a better way to do this, while retaining all the advantages of NMF -- such as interpretability, and being based on a simple biological intuition.
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 4
- Examples that run
- 100%4 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- Help pages citing references
- 75%
Downloads
Dependencies
Installing SpNMF adds 33 packages (15 with compiled code, 33 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, colorspace 2.0 MB. 1 more not on CRAN is not measured.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- 0.1.1Latest
- 0.1.02018-10-01
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2018-10-01
- Total releases
- 2 / 8 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.2.3
- Bundled data
- 147 KB / 1 file
- Download size
- 155 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("SpNMF")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
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