scFates.tl.activation_lm¶
- scFates.tl.activation_lm(adata, root_milestone, milestones, fdr_cut=0.05, stf_cut=0.8, pseudotime_offset=0, n_map=1, copy=False, n_jobs=- 1, layer=None)¶
A more robust version of tl.activation.
This is considered to be a more robust version of
scFates.tl.activation(). The common path between the two fates is retained for analysis, each feature is tested for its upregulation along the path from progenitor to the fork, using the linear model \(g_{i} \sim\ pseudotime\).- Parameters
- adata :
AnnData Annotated data matrix.
- root_milestone
tip defining progenitor branch.
- milestones
tips defining the progenies branches.
- stf_cut :
float(default:0.8) fraction of projections when gene passed fdr < 0.05.
- pseudotime_offset :
float(default:0) consider cells to retain up to the pseudotime_fork-pseudotime_offset.
- n_map :
int(default:1) number of cell mappings from which to do the test.
- n_jobs
number of cpu processes used to perform the test.
- copy :
bool(default:False) Return a copy instead of writing to adata.
- layer
layer to use for the test
- adata :
- Returns
adata – if copy=True it returns or else add fields to adata:
- .uns[‘root_milestone->milestoneA<>milestoneB’][‘fork’][‘module’]
classify feature as ‘early’ or ‘late’.
- .uns[‘root_milestone->milestoneA<>milestoneB’][‘fork’][‘slope’]
slope calculated by the linear model.
- .uns[‘root_milestone->milestoneA<>milestoneB’][‘fork’][‘pval’]
pval resulting from linear model.
- .uns[‘root_milestone->milestoneA<>milestoneB’][‘fork’][‘fdr’]
corrected fdr value.
- .uns[‘root_milestone->milestoneA<>milestoneB’][‘fork’][‘prefork_signi’]
proportion of projections where fdr<0.05.
- Return type