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. 2014 Aug 22;15(1):283. doi: 10.1186/1471-2105-15-283

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© Jacobs et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Relative RMSE of the target concentration estimates under realistic assumptions and misclassification. The is estimated as the square root of the sum of the relative variance and squared relative bias for S=1000 simulated experiments of 8 replicates. As results are relative to the true concentration λ, the precision of different dilutions of the same sample can be assessed on the same scale. Results were plotted for different misclassification probabilities (FPR, FNR) with FPR = false positive rate = 1-specificity and FNR = false negative rate = 1-sensitivity and in the presence of pipette error and unequal partition size. When misclassification is limited, a relatively wide window of dilution exists in which high accuracy and precision can be achieved.

Inline graphic — Relative RMSE of the target concentration estimates under realistic assumptions and misclassification. The is estimated as the square root of the sum of the relative variance and squared relative bias for S=1000 simulated experiments of 8 replicates. As results are relative to the true concentration λ, the precision of different dilutions of the same sample can be assessed on the same scale. Results were plotted for different misclassification probabilities (FPR, FNR) with FPR = false positive rate = 1-specificity and FNR = false negative rate = 1-sensitivity and in the presence of pipette error and unequal partition size. When misclassification is limited, a relatively wide window of dilution exists in which high accuracy and precision can be achieved.