M2SMF - Multi-Modal Similarity Matrix Factorization for Integrative Multi-Omics Data Analysis

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.

Last updated 5 years ago

2.23 score 17 scripts 181 downloads

M2SMJF - Multi-Modal Similarity Matrix Joint Factorization

A new method to implement clustering from multiple modality data of certain samples, the function M2SMjF() 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.

Last updated 4 years ago

2.00 score 2 scripts 169 downloads

OSNMTF - Orthogonal Sparse Non-Negative Matrix Tri-Factorization

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.

Last updated 5 years ago

2.00 score 2 scripts 126 downloads