snapatac2.pp.make_peak_matrix#
- snapatac2.pp.make_peak_matrix(adata, *, use_rep=None, inplace=False, file=None, backend='hdf5', peak_file=None, chunk_size=500, use_x=False, min_frag_size=None, max_frag_size=None, counting_strategy='paired-insertion')[source]#
Generate cell by peak count matrix.
This function will generate a cell by peak count matrix and store it in a new .h5ad file.
import_data
must be ran first in order to use this function.- Parameters:
adata (
AnnData
|AnnDataSet
) – The (annotated) data matrix of shapen_obs
xn_vars
. Rows correspond to cells and columns to regions.use_rep (
Union
[str
,list
[str
],None
]) – This is used to read peak information from.uns[use_rep]
. The peaks can also be provided by a list of strings: [“chr1:1-100”, “chr2:2-200”].inplace (
bool
) – Whether to add the tile matrix to the AnnData object or return a new AnnData object.file (
Optional
[Path
]) – File name of the output h5ad file used to store the result. If provided, result will be saved to a backed AnnData, otherwise an in-memory AnnData is used. This has no effect wheninplace=True
.backend (
Literal
['hdf5'
]) – The backend to use for storing the result. IfNone
, the default backend will be used.peak_file (
Optional
[Path
]) – Bed file containing the peaks. If provided, peak information will be read from this file.chunk_size (
int
) – Chunk sizeuse_x (
bool
) – If True, use the matrix stored in.X
as raw counts. Otherwise the.obsm['insertion']
is used.min_frag_size (
Optional
[int
]) – Minimum fragment size to include.max_frag_size (
Optional
[int
]) – Maximum fragment size to include.counting_strategy (
Literal
['fragment'
,'insertion'
,'paired-insertion'
]) – The strategy to compute feature counts. It must be one of the following: “fragment”, “insertion”, or “paired-insertion”. “fragment” means the feature counts are assigned based on the number of fragments that overlap with a region of interest. “insertion” means the feature counts are assigned based on the number of insertions that overlap with a region of interest. “paired-insertion” is similar to “insertion”, but it only counts the insertions once if the pair of insertions of a fragment are both within the same region of interest [Miao24]. Note that this parameter has no effect if input are single-end reads.
- Returns:
An annotated data matrix of shape
n_obs
xn_vars
. Rows correspond to cells and columns to peaks. Iffile=None
, an in-memory AnnData will be returned, otherwise a backed AnnData is returned.- Return type:
AnnData | ad.AnnData | None
See also
Examples
>>> import snapatac2 as snap >>> data = snap.pp.import_data(snap.datasets.pbmc500(downsample=True), chrom_sizes=snap.genome.hg38, sorted_by_barcode=False) >>> peak_mat = snap.pp.make_peak_matrix(data, peak_file=snap.datasets.cre_HEA()) >>> print(peak_mat) AnnData object with n_obs × n_vars = 585 × 1154611 obs: 'n_fragment', 'frac_dup', 'frac_mito'