pyrovelocity.cytotrace#
- pyrovelocity.cytotrace.FNNLSa(XtX, Xty, tol=None)[source]#
Faster NNLS imported from https://github.com/delnatan/FNNLSa A fast non-negativity-constrained least squares algorithm. Journal of chemometrics
- pyrovelocity.cytotrace.align_diffrate(adatas, labels, field='condition', type='A', outfield='cytotrace', ax=None)[source]#
this is used for differentiation rate comparison across samples
- pyrovelocity.cytotrace.census_normalize(mat, count)[source]#
RNA-seq census normalization to correct cell lysis
- pyrovelocity.cytotrace.compare_cytotrace(adata, layer='all', cell_count=10, condition='age', solver='nnls', is_normalized=False, n_cores=4, top_n_genes=200)[source]#
Main interface of cytotrace reimplementation used for single dataset with multiple conditions
- pyrovelocity.cytotrace.compare_cytotrace_ncores(adata, layer='all', cell_count=10, condition='age', solver='nnls', is_normalized=False, ncores=4, batch_cell=2000)[source]#
Main interface of cytotrace reimplementation used for single dataset with multiple conditions
- pyrovelocity.cytotrace.compute_gcs(mat, count, top_n_genes=200)[source]#
Compute gene set enrichment scores by correlating gene count and gene expression
- pyrovelocity.cytotrace.compute_similarity1(A)[source]#
Compute pairwise correlation of all columns in matrices A
- pyrovelocity.cytotrace.compute_similarity2(O, P)[source]#
Compute pearson correlation between two matrices O and P using einstein summation
- Return type:
ndarray
- pyrovelocity.cytotrace.convert_to_markov(sim)[source]#
Convert the Pearson correlation to Markov matrix
TODO: use velocity graph to replace this markov matrix
- pyrovelocity.cytotrace.cytotrace(adata, layer='all', cell_count=10, solver='nnls', top_n_genes=200)[source]#
Main interface of cytotrace reimplementation used for single dataset with one condition
- pyrovelocity.cytotrace.cytotrace_ncore(adata, layer='all', cell_count=10, solver='nnls', ncores=4, batch_cell=3000, shuffle=3)[source]#
optimized version