DIP calculations and statistics (thunor.dip)

thunor.dip.adjusted_r_squared(r, n, p)

Calculate adjusted r-squared value from r value

Parameters:

  • r (float) – r value (between 0 and 1)

  • n (int) – number of sample data points

  • p (int) – number of free parameters used in fit

Returns:

Adjusted r-squared value

Return type:

float

thunor.dip.ctrl_dip_rates(df_controls)

Calculate control DIP rates

Parameters:

df_controls (pd.DataFrame) – Pandas DataFrame of control cell counts from a thunor.io.HtsPandas object

Returns:

Fitted control DIP rate values

Return type:

pd.DataFrame

thunor.dip.dip_rates(df_data, selector_fn=<function tyson1>)

Calculate DIP rates on a dataset

Parameters:

  • df_data (thunor.io.HtsPandas) – Thunor HTS dataset

  • selector_fn (function) – Selection function for choosing optimal DIP rate fit (default: tyson1()

Returns:

Two entry list, giving control DIP rates and experiment (non-control) DIP rates (both as Pandas DataFrames)

Return type:

list

thunor.dip.expt_dip_rates(df_doses, df_vals, selector_fn=<function tyson1>)

Calculate experiment (non-control) DIP rates

Parameters:

  • df_doses (pd.DataFrame) – Pandas DataFrame of dose values from a thunor.io.HtsPandas object

  • df_vals (pd.DataFrame) – Pandas DataFrame of cell counts from a thunor.io.HtsPandas object

  • selector_fn (function) – Selection function for choosing optimal DIP rate fit (default: tyson1()

Returns:

Fitted DIP rate values

Return type:

pd.DataFrame

thunor.dip.tyson1(adj_r_sq, rmse, n)

Tyson1 algorithm for selecting optimal DIP rate fit

Parameters:

  • adj_r_sq (float) – Adjusted r-squared value

  • rmse (float) – Root mean squared error of fit

  • n (int) – Number of data points used in fit

Returns:

Fit value (higher is better)

Return type:

float