bioneuralnet.utils.data

Functions

correlation_summary(df)	Compute summary statistics of the maximum pairwise correlation
explore_data_stats(omics_df[, name])	Print key statistics for an omics DataFrame including variance, zero fraction,
expression_summary(df)	Compute summary statistics for the mean expression of features
get_logger(name)	Retrieves a global logger configured to write to 'bioneuralnet.log' at the project root.
variance_summary(df[, low_var_threshold])	Compute summary statistics for column variances in the DataFrame
zero_fraction_summary(df[, high_zero_threshold])	Compute summary statistics for the fraction of zeros in each column

bioneuralnet.utils.data.correlation_summary(df: DataFrame) → dict

Compute summary statistics of the maximum pairwise correlation

bioneuralnet.utils.data.explore_data_stats(omics_df: DataFrame, name: str = 'Data') → None

Print key statistics for an omics DataFrame including variance, zero fraction,

bioneuralnet.utils.data.expression_summary(df: DataFrame) → dict

Compute summary statistics for the mean expression of features

bioneuralnet.utils.data.variance_summary(df: DataFrame, low_var_threshold: float = None) → dict

Compute summary statistics for column variances in the DataFrame

bioneuralnet.utils.data.zero_fraction_summary(df: DataFrame, high_zero_threshold: float = None) → dict

Compute summary statistics for the fraction of zeros in each column