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. 2019 Sep 18;9:13519. doi: 10.1038/s41598-019-50077-4

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© The Author(s) 2019

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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(a) Distributions of PdI for a range of aggregated/contaminated samples, demonstrating the need for a sample specific definition to identify the measurement of transient particles. These distributions also show that the PdI is a biased distribution, and as such, a three standard-deviations from the mean threshold for outliers would not be robust. (b) Histogram of a sparsely collected set of measurements for a sample of lysozyme. Whilst fitting using a least squares regression and a Gaussian model in (a) reliably allowed the statistics of sufficiently sampled data sets to be determined, an attempt to fit to a sparse data set is shown in blue but shows poor correlation with the distribution data due to apparent under sampling. Also shown is a scatter plot of the individual values showing their spread. The individual point show in red is successfully identified as an outlier by the Rosner generalised many outlier procedure.