Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2020 Sep 8;11:4469. doi: 10.1038/s41467-020-18169-2

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

© 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 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/.

PMC Copyright notice

Fig. 1 — a The tumor sample is heterogeneous, composed of both normal cells and tumor subclones (top panel). The tumor dynamically evolves throughout the disease course, generating subclones with different genotypes (bottom panel). The dots in different colors represent different SNVs. b DNA-sequencing of the bulk tumor provides information about (1) allele frequency of each SNV (β), that is, the observed allele occurrence among all cells (top panel); (2) a CNA profile in the form of N_major and N_minor (bottom panel). Each of the yellow dots represents a copy of the allele with a certain SNV. c FastClone model. First, we calculated the proportion of cells that carry each SNV (ρ_i for SNV_i). This calculation is discussed in two situations: with and without CNA events. Multiple possibilities are further discussed (see Fig. 2). Blue spheres represent normal loci, and red spheres represent mutated loci that contain SNVs. Then, subclone numbers, subclone proportions, and tumor purity are determined from the distribution of ρ. After that, SNVs are assigned to subclones. Finally, the putative evolutionary relationship of the subclones is established. d The workflow of FastClone algorithm. The workflow starts with sequencing information as input, which includes allele frequency (β) and CNA profile (N_major and N_minor). Since we do not know the order of occurrence of genomic events, all possible scenarios are discussed, and ρ value for each scenario is calculated separately. The number of possible scenarios equals the value of N_major. Then, KDE is used to determine the distribution of ρ. Each peak in the ρ distribution indicates a subclone. After that, association scores between each SNV–subclone pair are calculated. Then, the SNV is assigned to the subclone with the highest association score. If there are several ρ values associated with one SNV, then the ρ that provides the highest association score is used to assign the SNV to the subclone (in this case, ρ₂ that assigns this SNV to the green subclone is considered the correct solution). Finally, the most likely phylogeny tree of the subclones is constructed.