TY - JOUR
T1 - Uphyloplot2
T2 - visualizing phylogenetic trees from single-cell RNA-seq data
AU - Kurtenbach, Stefan
AU - Cruz, Anthony M.
AU - Rodriguez, Daniel A.
AU - Durante, Michael A.
AU - Harbour, J. William
N1 - Funding Information:
This work was supported by Melanoma Research Foundation Career Development Award (Kurtenbach) and Established Investigator Award (Harbour), National Cancer Institute grant R01 CA125970 (Harbour), A Cure in Sight Jack Odell-John Dagres Research Award (Kurtenbach, Harbour), Bankhead-Coley Research Program of the State of Florida (Harbour), The Helman Family-Melanoma Research Alliance Team Science Award (Harbour) and a generous gift from Dr. Mark J. Daily (Harbour). The Bascom Palmer Eye Institute received funding from NIH Core Grant P30EY014801 and a Research to Prevent Blindness Unrestricted Grant. The Sylvester Comprehensive Cancer Center also received funding from the National Cancer Institute Core Support Grant P30CA240139. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/12
Y1 - 2021/12
N2 - Background: 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. Results: 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/. Conclusions: Uphyloplot2 is an easy-to-use tool to generate phylogenetic plots to depict tumor clonality from scRNA-seq data and other sources.
AB - Background: 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. Results: 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/. Conclusions: Uphyloplot2 is an easy-to-use tool to generate phylogenetic plots to depict tumor clonality from scRNA-seq data and other sources.
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U2 - 10.1186/s12864-021-07739-3
DO - 10.1186/s12864-021-07739-3
M3 - Article
C2 - 34090344
AN - SCOPUS:85107201188
SN - 1471-2164
VL - 22
JO - BMC Genomics
JF - BMC Genomics
IS - 1
M1 - 419
ER -