arcfish.tl.AxisWiseF#

class arcfish.tl.AxisWiseF(adata: AnnData)#

Perform axis-wise F-test and combine p-values by aggregated Cauchy test.

Parameters:: adata (AnnData) – adata of a single chromosome, created by arcfish.pp.FOF_CT_Loader.create_adata().

Methods

`__init__`(adata)
`append_pval`(result, cut_lo, cut_up, outer_cut)	Perform tests in each axis.
`append_summit`(result)	Treat the entry with the smallest p-value in each cluster as the summit.
`ij_background`(i, j, d1d, outer_cut)	The entries that are between 25kb and outer_cut away from the (i,j) entry are treated as the background.

static ij_background(i: int, j: int, d1d: ndarray, outer_cut: int) → ndarray#

The entries that are between 25kb and outer_cut away from the (i,j) entry are treated as the background.

Parameters:

i (int) – Index of the first locus.
j (int) – Index of the second locus.
d1d ((p,) np.ndarray) – Array of 1D genomic locations of imaging loci.
outer_cut (int) – Loci with 1D genomic distance within outer_cut from the target locus is included in the local background.

Returns:

A boolean matrix with background entries equal to True.

Return type:

(p, p) np.ndarray

append_pval(result: dict, cut_lo: int, cut_up: int, outer_cut: int)#

Perform tests in each axis. In addition to stat and pval, also append axis_stat and axis_pval, which are both (3,p,p) arrays.

Parameters:

result (dict) – The result dictionary to add testing results.
cut_lo (float) – Minimum loop size.
cut_up (float) – Maximum loop size.
outer_cut (int) – Loci with 1D genomic distance within outer_cut from the target locus is included in the local background.

append_summit(result: dict)#

Treat the entry with the smallest p-value in each cluster as the summit. No additional filtering.