clonealign: statistical integration of independent single-cell RNA and DNA sequencing data from human cancers Campbell, Kieran R.; Steif, Adi; Laks, Emma; Zahn, Hans; Lai, Daniel; McPherson, Andrew; Farahani, Hossein; Kabeer, Farhia; O’Flanagan, Ciara; Biele, Justina; et al.
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.
Item Citations and Data
Attribution 4.0 International (CC BY 4.0)