Work

Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) inference based on single cell copy number profile v1

Year: 2020

Type: preprint

Abstract: This protocol describes two innovative algorithms: 1) A minimal event distance aneuploidy lineage tree (MEDALT) inference algorithm allows implementing genetically meaningful distances and is scalable to current single-cell datasets containing thousands of cells, and 2) A statistical routine, Lineage Speciation Analysis (LSA), enables prioritization of CNAs and genes that are non-randomly associated with the observed lineage expansion and thereby are potentially functionally important.

DOI: 10.17504/protocols.io.bfhpjj5n

Authors: Fang Wang, Qihan Wang, Vakul Mohanty, Shaoheng Liang, Jinzhuang Dou, Jincheng Han, Darlan Conterno Minussi, Ruli Gao, Li Ding, Nicholas Navin, Ken Chen

Institutions: Houston Methodist, The University of Texas MD Anderson Cancer Center, Rice University

Language: English

Topic: Cancer Genomics and Diagnostics

Subfield: Cancer Research

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

OpenAlex ID: W3026744932

Cites:

Cited by: 1

Related to: 10