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Genome Biol. 2019 Mar 12;20(1):54. doi: 10.1186/s13059-019-1645-z.

clonealign: statistical integration of independent single-cell RNA and DNA sequencing data from human cancers.

Author information

1
Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.
2
Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada.
3
UBC Data Science Institute, University of British Columbia, Vancouver, British Columbia, Canada.
4
Genome Science and Technology Graduate Program, University of British Columbia, Vancouver, British Columbia, Canada.
5
Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada.
6
Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
7
CRUK IMAXT Grand Challenge Consortium, Cambridge, UK.
8
Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada. shahs3@mskcc.org.
9
Computational Oncology, Dept. of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA. shahs3@mskcc.org.
10
Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada. shahs3@mskcc.org.

Abstract

Measuring gene expression of tumor clones at single-cell resolution links functional consequences to somatic alterations. Without scalable methods to simultaneously assay DNA and RNA from the same single cell, parallel single-cell DNA and RNA measurements from independent cell populations must be mapped for genome-transcriptome association. We present clonealign, which assigns gene expression states to cancer clones using single-cell RNA and DNA sequencing independently sampled from a heterogeneous population. We apply clonealign to triple-negative breast cancer patient-derived xenografts and high-grade serous ovarian cancer cell lines and discover clone-specific dysregulated biological pathways not visible using either sequencing method alone.

PMID:
30866997
DOI:
10.1186/s13059-019-1645-z
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