MEDALT: single-cell copy number lineage tracing enabling gene discovery

Abstract We present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles, and a statistical routine named lineage speciation analysis (LSA), whichty facilitates discovery of fitness...

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Main Authors:	Fang Wang, Qihan Wang, Vakul Mohanty, Shaoheng Liang, Jinzhuang Dou, Jincheng Han, Darlan Conterno Minussi, Ruli Gao, Li Ding, Nicholas Navin, Ken Chen
Format:	Article
Language:	English
Published:	BMC 2021-02-01
Series:	Genome Biology
Subjects:	Single-cell scDNA-seq scRNA-seq Copy number alteration Tumor evolution Lineage tracing
Online Access:	https://doi.org/10.1186/s13059-021-02291-5

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spelling	doaj-a64148ff625b4189bbca527a4ac300112021-02-23T09:32:51ZengBMCGenome Biology1474-760X2021-02-0122112210.1186/s13059-021-02291-5MEDALT: single-cell copy number lineage tracing enabling gene discoveryFang Wang0Qihan Wang1Vakul Mohanty2Shaoheng Liang3Jinzhuang Dou4Jincheng Han5Darlan Conterno Minussi6Ruli Gao7Li Ding8Nicholas Navin9Ken Chen10Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer CenterDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer CenterDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer CenterDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer CenterDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer CenterDepartment of Cancer Biology, The University of Texas MD Anderson Cancer CenterDepartment of Genetics, The University of Texas MD Anderson Cancer CenterDepartment of Cardiovascular Sciences, Center for Bioinformatics and Computational Biology, Houston Methodist Research InstituteDepartment of Medicine, McDonnell Genome Institute Washington University School of MedicineDepartment of Genetics, The University of Texas MD Anderson Cancer CenterDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer CenterAbstract We present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles, and a statistical routine named lineage speciation analysis (LSA), whichty facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. MEDALT appears more accurate than phylogenetics approaches in reconstructing copy number lineage. From data from 20 triple-negative breast cancer patients, our approaches effectively prioritize genes that are essential for breast cancer cell fitness and predict patient survival, including those implicating convergent evolution. The source code of our study is available at https://github.com/KChen-lab/MEDALT .https://doi.org/10.1186/s13059-021-02291-5Single-cellscDNA-seqscRNA-seqCopy number alterationTumor evolutionLineage tracing
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Fang Wang Qihan Wang Vakul Mohanty Shaoheng Liang Jinzhuang Dou Jincheng Han Darlan Conterno Minussi Ruli Gao Li Ding Nicholas Navin Ken Chen
spellingShingle	Fang Wang Qihan Wang Vakul Mohanty Shaoheng Liang Jinzhuang Dou Jincheng Han Darlan Conterno Minussi Ruli Gao Li Ding Nicholas Navin Ken Chen MEDALT: single-cell copy number lineage tracing enabling gene discovery Genome Biology Single-cell scDNA-seq scRNA-seq Copy number alteration Tumor evolution Lineage tracing
author_facet	Fang Wang Qihan Wang Vakul Mohanty Shaoheng Liang Jinzhuang Dou Jincheng Han Darlan Conterno Minussi Ruli Gao Li Ding Nicholas Navin Ken Chen
author_sort	Fang Wang
title	MEDALT: single-cell copy number lineage tracing enabling gene discovery
title_short	MEDALT: single-cell copy number lineage tracing enabling gene discovery
title_full	MEDALT: single-cell copy number lineage tracing enabling gene discovery
title_fullStr	MEDALT: single-cell copy number lineage tracing enabling gene discovery
title_full_unstemmed	MEDALT: single-cell copy number lineage tracing enabling gene discovery
title_sort	medalt: single-cell copy number lineage tracing enabling gene discovery
publisher	BMC
series	Genome Biology
issn	1474-760X
publishDate	2021-02-01
description	Abstract We present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles, and a statistical routine named lineage speciation analysis (LSA), whichty facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. MEDALT appears more accurate than phylogenetics approaches in reconstructing copy number lineage. From data from 20 triple-negative breast cancer patients, our approaches effectively prioritize genes that are essential for breast cancer cell fitness and predict patient survival, including those implicating convergent evolution. The source code of our study is available at https://github.com/KChen-lab/MEDALT .
topic	Single-cell scDNA-seq scRNA-seq Copy number alteration Tumor evolution Lineage tracing
url	https://doi.org/10.1186/s13059-021-02291-5
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MEDALT: single-cell copy number lineage tracing enabling gene discovery

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