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M2SMF (version 2.0)

Multi-Modal Similarity Matrix Factorization for Integrative Multi-Omics Data Analysis

Description

A new method to implement clustering from multiple modality data of certain samples, the function M2SMF() jointly factorizes multiple similarity matrices into a shared sub-matrix and several modality private sub-matrices, which is further used for clustering. Along with this method, we also provide function to calculate the similarity matrix and function to evaluate the best cluster number from the original data.

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Version

Install

install.packages('M2SMF')

Monthly Downloads

196

Version

2.0

License

GPL (>= 2)

Maintainer

Xiaoyao Yin

Last Published

November 17th, 2019

Functions in M2SMF (2.0)

new_modularity

Calculate the modularity
dist2eu

Calculate the Euclidean distance
dist2bin

Calculate the agreement-based measurement
cost

Calculate the cost
update_L

the function to update Li, for i=1,2,...,N
Standard_Normalization

Normalize the input matrix by column
update_alpha

the function to update alpha
affinityMatrix

To calculate the similarity matrix
initialization

initialize the sub-matrix Ci into alpha*Li by SVD
M2SMF

the main part for M2SMF and clustering result
Cal_NMI

calculate the normalized mutual information.
initialize_WL

Initialize from the similairty matrix list
dist2chi

Calculate the chi-squared distance
simu_data_gen

Generate simulated data