mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-09-16 21:37:59 +08:00
2da62720dd
Removed the REST v2.0 documentation in favor of getting v1.0 working with driver/engine model
82 lines
2.3 KiB
Python
82 lines
2.3 KiB
Python
from abc import ABCMeta, abstractmethod
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class CXGDriver(metaclass=ABCMeta):
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def __init__(self, data, schema=None, graph_method=None, diffexp_method=None):
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self.data = self._load_data(data)
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@staticmethod
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@abstractmethod
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def _load_data(data):
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pass
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@abstractmethod
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def _load_or_infer_schema(data):
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pass
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@abstractmethod
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def cells(self):
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pass
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@abstractmethod
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def genes(self):
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pass
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@abstractmethod
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def filter_cells(self, filter):
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"""
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Filter cells from data and return a subset of the data
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A filter is a dictionary where the key is a metadatata category
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Value is dictionary
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value_type: int, float, string
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variable_type: continuous, categorical
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query: filter value, for categorical [val1, val2], for continuous {min: x, max:y}
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Filters are combined with the and operator
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:param filter:
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:return: filtered dataframe
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"""
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pass
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@abstractmethod
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def metadata(self, df, fields=None):
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"""
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Gets metadata key:value for each cells
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:param df: from filter_cells, dataframe
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:param fields: list of keys for metadata to return, returns all metadata values if not set.
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:return: list of metadata values
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"""
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pass
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@abstractmethod
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def create_graph(self, df):
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"""
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Computes a n-d layout for cells through dimensionality reduction.
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:param df: from filter_cells, dataframe
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:return: [cellid, x, y]
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"""
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pass
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@abstractmethod
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def diffexp(self, df1, df2):
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"""
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Computes the top differentially expressed genes between two clusters
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:param df1: from filter_cells, dataframe containing first set of cells
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:param df2: from filter_cells, dataframe containing second set of cells
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:return: top genes, stats and expression values for top genes
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"""
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pass
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@abstractmethod
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def expression(self, df):
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"""
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Retrieves expression for each gene for cells in data frame
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:param df:
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:return: {
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"genes": list of genes,
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"cells": list of cells and expression list,
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"nonzero_gene_count": number of nonzero genes
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}
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"""
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pass
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