pypairs.pairs.sandbag¶

pypairs.pairs.sandbag(data, annotation=None, gene_names=None, sample_names=None, fraction=0.65, filter_genes=None, filter_samples=None)¶

Calculate ‘marker pairs’ from a genecount matrix. Cells x Genes.

A Pair of genes (g1, g2) is considered a marker for a category if its expression changes from g1 > g2 in one category to g1 < g2 in all other categories, for at least a fraction of cells in this category.

data can be of type AnnData, DataFrame or ndarray and should contain the raw or normalized gene counts of shape n_obs * n_vars. Rows correspond to cells and columns to genes.

If data is AnnData object, the category for each sample should be in in data.vars['category'], gene names in data.var_names and sample names in data.obs_names.

If data is DataFrame object, gene names can be in df.columns or passed via gene_names and sample names in df.index or passed via sample_names. The category for each sample must be passed via annotation.

annotation must be in form of {‘category1’: [‘sample_1’,’sample_2’,…], …}. List of samples for indexing can be integer, str or a boolean mask of len(sample_names).

If data ndarray, all information must be passed via annotation, gene_names and sample_names parameters.

Marker pairs are returned as a mapping from category to list of 2-tuple Genes: {‘category’: [(Gene_1,Gene_2), …], …}

Parameters:	data : `Union`[`AnnData`, `DataFrame`, `ndarray`, `Collection`[`Collection`[`float`]]] The (annotated) data matrix of shape `n_obs` * `n_vars`. Rows correspond to cells and columns to genes. annotation : `Optional`[`Mapping`[`str`, `Collection`[`Union`[`str`, `int`, `bool`]]]] Mapping from category to genes. If `data` is not `AnnData`, this is required. List of genes can be index, names or logical mask. gene_names : `Optional`[`Collection`[`str`]] Names for genes, must be same length as `n_vars`. If `data` is not `AnnData`, this is required. sample_names : `Optional`[`Collection`[`str`]] Names for samples, must be same length as `n_obs`. If `data` is not `AnnData`, this is required. fraction : `float` Fraction of cells per category where marker criteria must be satisfied. Default: 0.65 filter_genes : `Optional`[`Collection`[`Union`[`str`, `int`, `bool`]]] A list of genes to keep. If not `None` all genes not in this list will be removed. List can be index, names or logical mask. filter_samples : `Optional`[`Collection`[`Union`[`str`, `int`, `bool`]]] A list of samples to keep. If not `None` all samples not in this list will be removed. List can be index, names or logical mask.
Return type:	`Mapping`[`str`, `Collection`[`Tuple`[`str`, `str`]]]
Returns:	marker_pairs_dict – A dict mapping from str to a list of 2-tuple, where the key is the category and the list contains the marker pairs: {‘Category_1’: [(Gene_1, Gene_2), …], …}.

Examples

To generate marker pairs for a different fraction than the default (0.65) based on the bundled oscope-dataset [Leng15] run:

from pypairs import pairs, datasets

adata = datasets.leng15()
marker_pairs = pairs.sandbag(adata, fraction=0.5)