Data from Reconstructing Complex Cancer Evolutionary Histories from Multiple Bulk DNA Samples Using Pairtree Article Swipe
Jeff Wintersinger
,
Stephanie M. Dobson
,
Ethan Kulman
,
Lincoln D. Stein
,
John E. Dick
,
Quaid Morris
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1158/2643-3230.c.6550547
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1158/2643-3230.c.6550547
Cancers are composed of genetically distinct subpopulations of malignant cells. DNA-sequencing data can be used to determine the somatic point mutations specific to each population and build clone trees describing the evolutionary relationships between them. These clone trees can reveal critical points in disease development and inform treatment. Pairtree is a new method that constructs more accurate and detailed clone trees than previously possible using variant allele frequency data from one or more bulk cancer samples. It does so by first building a Pairs Tensor that captures the evolutionary relationships between pairs of subpopulations, and then it uses these relations to constrain clone trees and infer violations of the infinite sites assumption. Pairtree can accurately build clone trees using up to 100 samples per cancer that contain 30 or more subclonal populations. On 14 B-progenitor acute lymphoblastic leukemias, Pairtree replicates or improves upon expert-derived clone tree reconstructions.Significance:Clone trees illustrate the evolutionary history of a cancer and can provide insights into how the disease changed through time (e.g., between diagnosis and relapse). Pairtree uses DNA-sequencing data from many samples of the same cancer to build more detailed and accurate clone trees than previously possible.See related commentary by Miller, p. 176.This article is highlighted in the In This Issue feature, p. 171.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1158/2643-3230.c.6550547
- OA Status
- gold
- Cited By
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- OpenAlex ID
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https://openalex.org/W4362525244Canonical identifier for this work in OpenAlex
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https://doi.org/10.1158/2643-3230.c.6550547Digital Object Identifier
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Data from Reconstructing Complex Cancer Evolutionary Histories from Multiple Bulk DNA Samples Using PairtreeWork title
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preprintOpenAlex work type
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enPrimary language
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2023Year of publication
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2023-04-04Full publication date if available
- Authors
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Jeff Wintersinger, Stephanie M. Dobson, Ethan Kulman, Lincoln D. Stein, John E. Dick, Quaid MorrisList of authors in order
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https://doi.org/10.1158/2643-3230.c.6550547Publisher landing page
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goldOpen access status per OpenAlex
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https://doi.org/10.1158/2643-3230.c.6550547Direct OA link when available
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clone (Java method), Biology, Genetics, Population, Cancer, Computational biology, Allele, DNA sequencing, Tree (set theory), DNA, Evolutionary biology, Gene, Mathematics, Combinatorics, Medicine, Environmental healthTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2024: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.reconstructions.</p>Significance:<p>Clone | 146 |
| abstract_inverted_index.176</a>.</i></p><p><i><a | 200 |
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| abstract_inverted_index.href="https://aacrjournals.org/bloodcancerdiscov/article/doi/10.1158/2643-3230.BCD-3-3-ITI" | 201 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.68056735 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |