Please turn to runINMF or runIntegration.
Perform integrative non-negative matrix factorization to return factorized H, W, and V matrices. It optimizes the iNMF objective function using block coordinate descent (alternating non-negative least squares), where the number of factors is set by k. TODO: include objective function equation here in documentation (using deqn)
For each dataset, this factorization produces an H matrix (cells by k), a V matrix (k by genes), and a shared W matrix (k by genes). The H matrices represent the cell factor loadings. W is held consistent among all datasets, as it represents the shared components of the metagenes across datasets. The V matrices represent the dataset-specific components of the metagenes.
liger object with H, W, and V slots set.
liger object. Should normalize, select genes, and scale
before calling.
Inner dimension of factorization (number of factors). Run suggestK to determine appropriate value; a general rule of thumb is that a higher k will be needed for datasets with more sub-structure.
Regularization parameter. Larger values penalize dataset-specific effects more strongly (ie. alignment should increase as lambda increases). Run suggestLambda to determine most appropriate value for balancing dataset alignment and agreement (default 5.0).
Convergence threshold. Convergence occurs when |obj0-obj|/(mean(obj0,obj)) < thresh. (default 1e-6)
Maximum number of block coordinate descent iterations to perform (default 30).
Number of restarts to perform (iNMF objective function is non-convex, so taking the best objective from multiple successive initializations is recommended). For easier reproducibility, this increments the random seed by 1 for each consecutive restart, so future factorizations of the same dataset can be run with one rep if necessary. (default 1)
Initial values to use for H matrices. (default NULL)
Initial values to use for W matrix (default NULL)
Initial values to use for V matrices (default NULL)
Random seed to allow reproducible results (default 1).
Print objective function values after convergence (default FALSE).
Print progress bar/messages (TRUE by default)
Arguments passed to other methods
rliger-deprecated