scFates.tl.test_covariate¶
- scFates.tl.test_covariate(adata, group_key, features=None, seg=None, layer=None, trend_test=False, fdr_cut=0.01, n_jobs=1, n_map=1, copy=False)¶
Test for branch differential gene expression between covariates on the same trajectory path.
Test of amplitude difference
The same is used as in
scFates.tl.test_fork()
. This uses the following model :\(g_{i} \sim\ s(pseudotime)+s(pseudotime):Covariate+Covariate\)
Where \(s(.)\) denotes the penalized regression spline function and \(s(pseudotime):Covariate\) denotes interaction between the smoothed pseudotime and covariate terms. From this interaction term, the p-value is extracted.
Test of trend difference
Inspired from a preprint [Ji22], this test compares the following full model:
\(g_{i} \sim\ s(pseudotime)+s(pseudotime):Covariate+Covariate\)
to the following reduced one:
\(g_{i} \sim\ s(pseudotime)+s(pseudotime)+Covariate\)
Comparison is done using ANOVA
- Parameters
- adata :
AnnData
Annotated data matrix.
- group_key :
str
key in .obs for the covariates to test.
- features :
Iterable
|None
Optional
[Iterable
] (default:None
) Which features to test (all significants by default).
- seg :
str
|None
Optional
[str
] (default:None
) In the case of a tree, which segment to use for such test.
- layer :
str
|None
Optional
[str
] (default:None
) layer to use for the test
- trend_test :
bool
(default:False
) Whether to perform the trend test instead of amplitude test.
- n_jobs :
int
(default:1
) number of cpu processes used to perform the test.
- n_map :
int
(default:1
) number of cell mappings from which to do the test (not implemented yet).
- copy :
bool
(default:False
) Return a copy instead of writing to adata.
- adata :
- Returns
adata – if copy=True it returns or else add fields to adata:
- .var[‘cov_pval’ or ‘covtrend_pval’]
pvalues extracted from tests.
- .var[‘cov_fdr’ or ‘covtrend_fdr’]
FDR extracted from the pvalues.
- .var[‘cov_signi’ or ‘covtrend_signi’]
is the feature significant.
- .var[‘A->B_lfc’]
logfoldchange in expression between covariate A and B.
- Return type