PairwiseComparisonTTestFC#

class omicspylib.analysis.pairs.statistical.PairwiseComparisonTTestFC(dataset: ProteinsDataset, condition_a: str, condition_b: str)#

Perform pairwise comparison between two groups, using a t-test and a fold change rule.

__init__(dataset: ProteinsDataset, condition_a: str, condition_b: str)#
eval(min_frequency: int = 3, na_threshold: float = 0.0, pval_adj_method: Literal['bonferroni', 'sidak', 'holm-sidak', 'holm', 'simes-hochberg', 'hommel', 'fdr_bh', 'fdr_by', 'fdr_tsbh', 'fdr_tsbky'] | None = 'fdr_bh', use_log_transformed: bool = True)#

Perform the pairwise comparison between the two groups, using a t-test and a fold change rule. By default, quantitative values are log2 transformed, prior to t-test calculation. For the fold change calculation, the original values are used.

Parameters:

  • min_frequency (int, optional) – Records identified in less than this number of biological repeats, in a given experimental condition, will be excluded from the analysis.

  • na_threshold (float, optional) – Values equal or below this threshold are considered missing.

  • pval_adj_method (str or None, optional) – Method to adjust p-values for multiple hypothesis testing error. If not provided, no adjustment will be performed.

  • use_log_transformed (bool, optional) – By default, quantitative values are log2 transformed prior to t-test. If set to False this transformation will be omitted.

Returns:

A Pandas data frame with the results of the t-test and fold change calculations. Use the data frame index to join back the results with the dataset.

Return type:

pd.DataFrame