Package: M3JF 0.1.0

Xiaoyao Yin

M3JF: Multi-Modal Matrix Joint Factorization for Integrative Multi-Omics Data Analysis

Multi modality data matrices are factorized conjointly into the multiplication of a shared sub-matrix and multiple modality specific sub-matrices, group sparse constraint is applied to the shared sub-matrix to capture the homogeneous and heterogeneous information, respectively. Then the samples are classified by clustering the shared sub-matrix with kmeanspp(), a new version of kmeans() developed here to obtain concordant results. The package also provides the cluster number estimation by rotation cost. Moreover, cluster specific features could be retrieved using hypergeometric tests.

Authors:Xiaoyao Yin [aut, cre]

M3JF_0.1.0.tar.gz
M3JF_0.1.0.tar.gz(r-4.7-any)M3JF_0.1.0.tar.gz(r-4.6-any)
M3JF_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
M3JF/json (API)

# Install 'M3JF' in R:

install.packages('M3JF', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 3 scripts 255 downloads 13 exports 50 dependencies

Last updated from:796c977d15. Checks:4 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	162
source / vignettes	OK	177
linux-release-x86_64	OK	154
wasm-release	OK	156

Exports:cost crimmix_data_gen feature_screen_sd feature_selection initialize_WL iNMF_data_gen intersim_data_gen kmeanspp M3JF RotationCostBestGivenGraph simulateY update_E update_H

Dependencies:alluvial Biobase BiocGenerics BiocManager cli cluster codetools colorspace cpp11 digest doParallel dplyr ExPosition farver foreach generics ggplot2 glue gridBase gtable InterSIM isoband iterators labeling lifecycle magrittr MASS NMF pillar pkgconfig plyr prettyGraphs R6 RColorBrewer Rcpp registry reshape2 rlang rngtools S7 scales SNFtool stringi stringr tibble tidyselect utf8 vctrs viridisLite withr

An Introduction to the package M3JF

Installation | Usage | Simulation data generation | Simulation data groundtruth assignment and permutation | You should start from here if you are using your own data. | You can ommit the following if you do not have any true label as the groudtruth, we do the next to evaluate our method.

Rendered fromintroduction.Rmdusingknitr::rmarkdown

Last update: 2023-08-14
Started: 2023-08-14

Help page	Topics
Calculate the cost defined by the objective function	cost
Generate the simulated dataset with three modalities with the package crimmix	crimmix_data_gen
Screen the cluster related features via hypergeometric test p value and distribution standard derivation	feature_screen_sd
Select the cluster related features via hypergeometric test	feature_selection
Initialize the shared sub-matrix E and modality specific sub-matrices list Hi	initialize_WL
Generate the simulated dataset with three modalities as the work iNMF	iNMF_data_gen
Generate the simulated dataset with three modalities with the package InterSIM	intersim_data_gen
A new version of kmeans that generates stable cluster result	kmeanspp
Multi-Modal Matrix Joint Factorization	M3JF
Evaluate the cluster number of multiple modality data	RotationCostBestGivenGraph
Generate the simulated dataset with specified parameters	simulateY
Update sub-matrix E	update_E
Update sub-matrices list Hi	update_H

Package: M3JF 0.1.0

M3JF: Multi-Modal Matrix Joint Factorization for Integrative Multi-Omics Data Analysis

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