Uphyloplot2: visualizing phylogenetic trees from single-cell RNA-seq data

Recent advances in single cell sequencing technologies allow for greater resolution in assessing tumor clonality using chromosome copy number variations (CNVs). While single cell DNA sequencing technologies are ideal to identify tumor sub-clones, they remain expensive and in contrast to single cell...

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Bibliographic Details
Published in:BMC genomics 2021-06, Vol.22 (1), p.419-419, Article 419
Main Authors: Kurtenbach, Stefan, Cruz, Anthony M, Rodriguez, Daniel A, Durante, Michael A, Harbour, J William
Format: Article
Language:English
Subjects:
Analysis
Cancer
Carcinogenesis
Chromosomes
Copy number
Deoxyribonucleic acid
DNA
DNA Copy Number Variations
DNA sequencing
Error analysis
Exports
Gene expression
Gene Expression Profiling
Genomes
Genomics
Melanoma
Mutation
Phylogenetic trees
Phylogenetics
Phylogeny
Programming languages
Ribonucleic acid
RNA
RNA sequencing
RNA-Seq
Sequence Analysis, RNA
Single-Cell Analysis
Software
Tumors
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Summary:Recent advances in single cell sequencing technologies allow for greater resolution in assessing tumor clonality using chromosome copy number variations (CNVs). While single cell DNA sequencing technologies are ideal to identify tumor sub-clones, they remain expensive and in contrast to single cell RNA-seq (scRNA-seq) methods are more limited in the data they generate. However, CNV data can be inferred from scRNA-seq and bulk RNA-seq, for which several tools have been developed, including inferCNV, CaSpER, and HoneyBADGER. Inferences regarding tumor clonality from CNV data (and other sources) are frequently visualized using phylogenetic plots, which previously required time-consuming and error-prone, manual analysis. Here, we present Uphyloplot2, a python script that generates phylogenetic plots directly from inferred RNA-seq data, or any Newick formatted dendrogram file. The tool is publicly available at https://github.com/harbourlab/UPhyloplot2/ . Uphyloplot2 is an easy-to-use tool to generate phylogenetic plots to depict tumor clonality from scRNA-seq data and other sources.
ISSN:1471-2164
1471-2164
DOI:10.1186/s12864-021-07739-3