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. 2022 Mar 8;13:1205. doi: 10.1038/s41467-022-28845-0

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© The Author(s) 2022

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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Fig. 1 — a Schematic for tailored analysis suite recommended to use alongside MQuad. Precision-Recall (PR) curve (b) and Receiver Operating Characteristic (ROC) curve (c) for the detection of simulated variants in a simulation with all default settings (see Methods) except 50 clonal variants per clone. Curve is generated by varying the cutoff on ΔBIC in MQuad, VMR in mgatk, and MPR in Monovar. Black circle and triangle represent the default thresholds used to classify informative variants for MQuad and mgatk respectively. The threshold for Monovar is not shown because there is no default threshold suggested. d Cumulative distribution function of ΔBIC with cutoff shown, based on the same data in b, c. Changes in area under PR curve (AUPRC) and area under ROC curve (AUROC) when varying (e) number of variants per clone, (f) allele frequency of clonal variants, (g) clone sizes, (h) evolutionary models. Asterisk indicates the default parameter.