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.
CITATION STYLE
Campbell, K. R., Steif, A., Laks, E., Zahn, H., Lai, D., McPherson, A., … Shah, S. P. (2019). Clonealign: Statistical integration of independent single-cell RNA and DNA sequencing data from human cancers. Genome Biology, 20(1). https://doi.org/10.1186/s13059-019-1645-z
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