Computer implemented method for analyzing host phage response data

A non-transitory, computer program product comprising computer executable instructions for analyzing host phage response data, the instructions executable by a computer for:

• receiving a host phage response dataset, wherein the dataset comprises a time series dataset for a host-phage combination in which a host bacteria is grown in the presence of a phage, and each data point in the time series dataset comprises a measurement of a parameter indicative of the growth of the host bacteria in the presence of the phage at a specific time;
• normalizing the time series dataset based on an associated control curve;
• obtaining an estimate of a lag time comprising:
• for a plurality of time points in a time window from an initial time point to an end time point, fitting one or more candidate functions over a fitting time window from the initial time point to a current time point, wherein fitting estimates a set of growth curve summary parameters comprising at least a lag time and a goodness of fit parameter;
• selecting a best fit function for the current time point from the one or more fitted candidate functions based on the goodness of fit parameters, wherein the one or more candidate functions each comprise a different functional form and at least one of which is a sigmoidal function, and when none of the goodness of fit estimates pass a threshold goodness of fit then classifying the time series dataset as flat and setting the lag time to the end time point;
• selecting from the plurality of time points, a best time point based on goodness of fit values at the plurality of time points;
• searching for an alternative best time point closer in time to, and greater than, a minimum time point than the best time fit and updating the best time point to the alternative best time point when the goodness of fit of the alternative time point is within a threshold amount of the goodness of fit of the best time point;
• and
• estimating a lag time for the best time point, wherein when the goodness of fit exceeds a threshold goodness of fit the lag time is obtained from the growth curve summary parameter otherwise classifying the time series dataset as flat and setting the lag time to the end time point;
• and
• reporting at least the lag time or a hold time calculated as the estimated lag time from which the lag time for a control is subtracted.

A computing apparatus comprising:

• at least one memory, and
• at least one processor wherein the memory comprises instructions to configure the at least one processor for:
• receiving a host phage response dataset, wherein the dataset comprises a time series dataset for a host-phage combination in which a host bacteria is grown in the presence of a phage, and each data point in the time series dataset comprises a measurement of a parameter indicative of the growth of the host bacteria in the presence of the phage at a specific time;
• normalizing the time series dataset based on an associated control curve;
• obtaining an estimate of a lag time comprising:
• for a plurality of time points in a time window from an initial time point to an end time point, fitting one or more candidate functions over a fitting time window from the initial time point to a current time point, wherein fitting estimates a set of growth curve summary parameters comprising at least a lag time and a goodness of fit parameter;
• selecting a best fit function for the current time point from the one or more fitted candidate functions based on the goodness of fit parameters, wherein the one or more candidate functions each comprise a different functional form and at least one of which is a sigmoidal function, and when none of the goodness of fit estimates pass a threshold goodness of fit then classifying the time series dataset as flat and setting the lag time to the end time point;
• selecting from the plurality of time points, a best time point based on goodness of fit values at the plurality of time points;
• searching for an alternative best time point closer in time to, and greater than, a minimum time point than the best time fit and updating the best time point to the alternative best time point when the goodness of fit of the alternative time point is within a threshold amount of the goodness of fit of the best time point;
• and
• estimating a lag time for the best time point, wherein when the goodness of fit exceeds a threshold goodness of fit the lag time is obtained from the growth curve summary parameter otherwise classifying the time series dataset as flat and setting the lag time to the end time point;
• and
• reporting at least the lag time or a hold time calculated as the estimated lag time from which the lag time for a control is subtracted.