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https://github.com/lockEF/bidifac
Bidimensional matrix factorization
https://github.com/lockEF/bidifac
Last synced: about 8 hours ago
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Bidimensional matrix factorization
- Host: GitHub
- URL: https://github.com/lockEF/bidifac
- Owner: lockEF
- Created: 2018-12-10T23:17:24.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2024-04-11T01:48:57.000Z (7 months ago)
- Last Synced: 2024-08-02T20:43:39.923Z (3 months ago)
- Language: R
- Size: 55.7 KB
- Stars: 3
- Watchers: 3
- Forks: 4
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-multi-omics - BIDIFAC - Park - bidimensional integrative factorization - [paper 1](https://doi.org/10.1111/biom.13141), [paper 2](https://arxiv.org/abs/2002.02601) (Software packages and methods / Multi-omics correlation or factor analysis)
README
# BIDIFAC
Bidimensional matrix factorizationR code to perform factorization and dimension reduction of bidimensionally linked data matrices [1]. The file BIDIFAC.R gives functions to perform the BIDIFAC factorization, simulate data, and perform missing value imputation using BIDIFAC. See BIDIFAC_example.R for example usage. Written by [Jun Young Park](https://www.statisticspark.com/).
[1] J Park and EF Lock. Integrative Factorization of Bidimensionally Linked Matrices. Biometrics, 2019. [(article link)](https://onlinelibrary.wiley.com/doi/abs/10.1111/biom.13141) [arXiv preprint: 1906.03722](https://arxiv.org/abs/1906.03722).
The functions bidifac.plus.R, bidifac.plus.impute.R, and bidifac.plus.given.R perform the BIDIFAC+ method, described in [2]. See bidifac.plus_example.R for example usage.
[2] EF Lock, J Park and KA Hoadley. Bidimensional linked matrix factorization for pan-omics pan-cancer analysis, Annals of Applied Statistics 2022. [(article link)](https://projecteuclid.org/journals/annals-of-applied-statistics/volume-16/issue-1/Bidimensional-linked-matrix-factorization-for-pan-omics-pan-cancer-analysis/10.1214/21-AOAS1495.short)
The functions in EV_Bidifac_Functions.R perform an empirical variational Bayes version of the decompostion, as described in [3]. See EV_Bidifac_Examples.R for example usage.
[3] Working preprint: https://ericfrazerlock.com/EVBIDI_Manuscript.pdf .