ase#
ASE data analysis with expression bias calculation
- class ase.ASEAnalysis#
Base class for ASE data analysis
- get_a_t()#
Returns the alternative and the total counts
- get_all(genes, min_t=0)#
Returns multiple calculated parameters
Parameters#
- genes: list(dict)
A list of gene dictionaries with elements ‘id’, ‘seq_region_name’, ‘start’ and ‘end’, like the ones obtained from Ensembl requests
- min_t: int
The minimum total count for SNPs considered for a cell
Returns#
- a, t: pd.DataFrame, pd.DataFrame
The alternative and the total counts per SNP (rows) and cell (cloumns)
- bij: pd.DataFrame
The calculated expression bias per SNP (rows) and cell (columns)
- snps: pd.DataFrame
The SNP chromosomes and positions
- bj: pd.DataFrame
The calculated expression bias per gene (rows) and cell (columns)
- bj_t: pd.DataFrame
The totac counts per gene (rows) and cell (columns)
- get_altcount_totcount()#
Returns the alternative and the total counts
- get_bias_per_gene(genes, min_t=0)#
Returns the calculated expression bias per gene and cell
Parameters#
- genes: list(dict)
A list of gene dictionaries with elements ‘id’, ‘seq_region_name’, ‘start’ and ‘end’, like the ones obtained from Ensembl requests
- min_t: int
The minimum total count for SNPs considered for a cell
Returns#
- bj: pd.DataFrame
The calculated expression bias per gene (rows) and cell (columns)
- bj_t: pd.DataFrame
The sum of weights per gene (rows) and cell (columns), which is the sum of total counts for the SNPs considered for a gene
- get_bias_per_snp()#
Returns the calculated expression bias per SNP and cell
- get_bij()#
Returns the calculated expression bias per SNP and cell
- get_bj(genes, min_t=0)#
Returns the calculated expression bias per gene and cell
Parameters#
- genes: list(dict)
A list of gene dictionaries with elements ‘id’, ‘seq_region_name’, ‘start’ and ‘end’, like the ones obtained from Ensembl requests
- min_t: int
The minimum total count for SNPs considered for a cell
Returns#
- bj: pd.DataFrame
The calculated expression bias per gene (rows) and cell (columns)
- bj_t: pd.DataFrame
The sum of weights per gene (rows) and cell (columns), which is the sum of total counts for the SNPs considered for a gene
- get_snps()#
Returns the SNP chromosomes and positions
- class ase.ASEMultipleDonorsAnalysis(analyses, n_cpu=None)#
Analyse ASE data for multiple donors
- get_a_t()#
Returns the alternative and the total counts
- get_bij()#
Returns the calculated expression bias per SNP and cell
- get_bj(genes, min_t=0)#
Returns the calculated expression bias per gene and cell
Parameters#
- genes: list(dict)
A list of gene dictionaries with elements ‘id’, ‘seq_region_name’, ‘start’ and ‘end’, like the ones obtained from Ensembl requests
- min_t: int
The minimum total count for SNPs considered for a cell
Returns#
- bj: pd.DataFrame
The calculated expression bias per gene (rows) and cell (columns)
- bj_t: pd.DataFrame
The sum of weights per gene (rows) and cell (columns), which is the sum of total counts for the SNPs considered for a gene
- get_snps()#
Returns the SNP chromosomes and positions
- class ase.ASESingleDonorAnalysis(a_file_paths, t_file_paths)#
Analyse ASE data for one donor
- get_a_t()#
Returns the alternative and the total counts
- get_bij()#
Returns the calculated expression bias per SNP and cell
- get_bj(genes, min_t=0)#
Returns the calculated expression bias per gene and cell
Parameters#
- genes: list(dict)
A list of gene dictionaries with elements ‘id’, ‘seq_region_name’, ‘start’ and ‘end’, like the ones obtained from Ensembl requests
- min_t: int
The minimum total count for SNPs considered for a cell
Returns#
- bj: pd.DataFrame
The calculated expression bias per gene (rows) and cell (columns)
- bj_t: pd.DataFrame
The sum of weights per gene (rows) and cell (columns), which is the sum of total counts for the SNPs considered for a gene
- get_snps()#
Returns the SNP chromosomes and positions
- ase.get_bias(bj, bj_t, cell_populations, min_t=0)#
Calculates mean and average expression bias
Parameters#
- bj: pd.DataFrame
The expression bias per gene (rows) and cell (columns)
- bj_t: pd.DataFrame
The total counts for the SNPs considered for a gene per gene (rows) and cell (columns)
- cell_poulations: dict(key: list(str))
A dictionary of cell populations with arbitrary keys and the cell ids of the cell populations as values
- min_t: int
The minimum total count for cells considered for the calculation of mean and average expression bias
Returns#
- b_mean: pd.DataFrame
The mean expression bias per gene (rows) and cell population (columns)
- b_variance: pd.DataFrame
The variance of mean expression bias per gene (rows) and cell population (columns)
- b_n: pd.DataFrame
The number of cells considered per gene (rows) and cell population (columns)
- b_average: pd.DataFrame
The average expression bias per gene (rows) and cell population (columns)
- b_t: pd.DataFrame
The total counts for the SNPs considered per gene (rows) and cell population (columns)
- b_cell_populations: dict(key: list(str))
A dictionary of cell populations with only the cells considered (after the cut on ‘min_t’)