Fig. 4
Examples of LLOQ determinations made using the baseline noise decision tree. The data is from the 3 replicates of miR-1 calibration curves run at one site on different days that covers the 3 options in the workflow. (a + b) Example of data that meets option 1: the NTC has a Cq value from which 3.32 is subtracted to derive a NTC + 10. The calibrator dilution with a Cq nearest the NTC + 10 is the LLOQ. (c + d) Example of data that meets option 2: the Cq for the lowest calibration curve point is undetermined. The lowest calibrator concentration is multiplied by 10 and the nearest calibrator concentration is the LLOQ. (e + f) Example of data using option 3. The concentration of the next unmeasured serial dilution point is calculated and multiplied by 10. The nearest measured calibrator concentration is the LLOQ. Black circles: calibration curve points. Red circles: NTC values. Red triangle: NTC + 10