Statistics of single-molecule measurements: applications in flow-cytometry sizing of DNA fragments.
BACKGROUND
The measurement of physical properties from single molecules has been demonstrated. However, the majority of single-molecule studies report values based on relatively large data sets (e.g., N > 50). While there are studies that report physical quantities based on small sample sets, there has not been a detailed statistical analysis relating sample size to the reliability of derived parameters.


METHODS
Monte Carlo simulations and multinomial analysis, dependent on quantifiable experimental parameters, were used to determine the minimum number of single-molecule measurements required to produce an accurate estimate of a population mean. Simulation results were applied to the fluorescence-based sizing of DNA fragments by ultrasensitive flow cytometry (FCM).


RESULTS
Our simulations show, for an analytical technique with a 10% CV, that the average of as few as five single-molecule measurements would provide a mean value within one SD of the population mean. Additional simulations determined the number of measurements required to obtain the desired number of replicates for each subpopulation within a mixture. Application of these results to flow cytometry data for lambda/HindIII and S. aureus Mu50/SmaI DNA digests produced accurate DNA fingerprints from as few as 98 single-molecule measurements.


CONCLUSIONS
A surprisingly small number of single-molecule measurements are required to obtain a mean measurement descriptive of a normally-distributed parent population.
Ferris
Matthew M
MM
Bioscience Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.
Habbersett
Robbert C
RC
Wolinsky
Murray
M
Jett
James H
JH
Yoshida
Thomas M
TM
Keller
Richard A
RA
D010582:Bacteriophage lambda / Q000737:chemistry*; D004247:DNA / Q000032:analysis*; D016172:DNA Fingerprinting / Q000379:methods / Q000706:statistics & numerical data*; D053938:DNA Fragmentation; D005434:Flow Cytometry / Q000379:methods / Q000706:statistics & numerical data*; D009010:Monte Carlo Method; D015203:Reproducibility of Results; D013211:Staphylococcus aureus / Q000737:chemistry*
D004247:DNA