Computing Synergy References#

xynergy.reference.add_reference(df, dose_cols, response_col, experiment_cols=None, method: list[str] | str = ['bliss', 'hsa', 'loewe', 'zip'], log: str = 'all')#

Add columns containing the reference for a given method.

Parameters#

df: polars.DataFrame

Usually the output from tidy or one of its downstream functions

dose_cols: list, default [“dose_a”, “dose_b”]

A list of exactly two columns names that contain untransformed numeric values of agent dose

response_col: string, default “response”

The name of the column containing responses

experiment_cols: list[str], string, or None, default “experiment_id”

The names of columns that should be used to distinguish one dose pair’s response from another. If none are supplied, two rows with the same doses will be considered replicates.

method: list[str] or str, default [“bliss”, “hsa”, “loewe”, “zip”]

The method used for calculating reference.

log: string, default “all”

Verbosity of function. Options include “all”, “warn”, and “none”.

  • If “all”, will emit notes and warnings.

  • If “warn”, will emit only warnings.

  • If “none”, will not emit anything (except errors)

Returns#

polars.DataFrame

Input with [method]_ref columns appended.

Warnings#

Subtracting the reference from the observed value is sometimes, but not always the same as calculating the synergy score. If what you want is a measure of deviation of the observed response from the expected response, prefer add_synergy

Notes#

Refer to add_synergy for details on individual synergy/reference models, such as their advantages, limitations, and how they are calculated