Method and device for analyzing a dataset

A computer-implemented method for analyzing a dataset, the method comprising a step of performing an analyzing assay and retrieving intensity values from said assay, wherein said analyzing assay comprises nucleic acid amplification by digital polymerase chain reaction (dPCR),

• wherein, in the digital PCR, the sample is separated into partitions, wherein a PCR reaction is carried out in each partition individually, wherein partitions containing a target nucleotide sequence are amplified and produce a positive detection signal, while the partitions containing no target nucleotide sequence are not amplified and produce no detection signal;
• further comprising the steps of:
• a) providing a dataset comprising a plurality of intensity values from a plurality of measurement samples;
• wherein said plurality of measurement samples are derived from a single biological test sample comprising nucleic acids;
• b) providing a predefined discrimination value for separating the intensity values into two different data categories;
• c) separating the plurality of intensity values into either one of the two different data categories by determining whether the individual values of the intensity values are above or below the predefined discrimination value;
• d) determining the cumulative probability function for all values in the data category above the discrimination value (Group A) and determining the cumulative probability function for all values in the data category below the discrimination value (Group B);
• e) obtaining a new discrimination values such that a ratio between the two cumulative probability functions corresponds to a predefined error factor;
• f) iterating steps c) to e)
• whereby the new discrimination value obtained in step e) after an iteration replaces the discrimination value of the previous iteration;
• and
• whereby the iteration is carried out until the compositions of data categories (Group A, positives and Group B, negatives) remain constant or for a predetermined number of iterations;
• and
• g) automatically providing the new discrimination value obtained in step f) of the last iteration as threshold for allocating intensity values derived from a digital PCR assay from the biological sample comprising nucleic acids into either data category, Group A positives and Group B negative.

The method of claim 1, wherein step e) comprises:

• i. determining the intersection point between the cumulative probability functions of step d);
• ii. calculating the probability of said intersection point deriving two new cumulative probability functions
• iii) multiplying or dividing said new cumulative probability functions by the square root of the predefined error factor and calculating two approximation points using inverse cumulative probability functions;
• v) interpolating the probability density function ratio of the approximation points thereby obtaining a new discrimination value.