NMF solver for gene programs.
Project description
Installation
$ pip install bionmf
Usage
from bionmf import BioNMF # Import model
model = BioNMF()
nmf = model.fit( # NMFInfo object
adata, # AnnData object
rank_range = range(2, 3),
n_runs = 3,
cutoff = 0.95
)
genes = model.program_genes() # Get differential expressed genes per program
model.plot_cophcorr() # Cophenetic correlation for each tested rank
model.plot_heatmap() # Heaetmap of gene programs
Documentation
BioNMF(
random_state, # Initial random state
**kwargs # Rest of arguments are passed to sklearn.decomposition.NMF
).fit(
adata, # Accepts AnnData and DataFrame (must be cells as rows)
rank_range, # Range of rank values to test
n_runs, # Number of runs (random intializations) for each rank
cutoff, # Cophenetic correlation cutoff
) # -> returns NMFInfo object
NMFInfo(
rank, # Best rank
W, # (genes by factors) matrix -> gene programs
H, # (cells by factors) matrix -> program assignment
connectivity_mat, # (cells by cells) matrix -> program connectivity
reconstruction_err, # RMSE of reconstruction
cophcorr, # Cophenetic correlation
)
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