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. 2020 Oct 6;10:16581. doi: 10.1038/s41598-020-73644-6

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© The Author(s) 2020

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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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Percentages of inliers (dark colours) and novelties/outliers (light colours) applying univariate (MD: Mahalanobis distance) and multivariate outlier detection methods to 56-dimensional model datasets HemoPI-1 (a), HemoPI-2 (b), HemoPI-3 (c) (in reds), Antimicrobial Peptide Dataset (APD, 3081—in blues) and known hemolytic antimicrobial peptides in APD (HAMP, 317—in greens).