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

clonealign:人类癌症独立单细胞 RNA 和 DNA 测序数据的统计整合

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作者:Kieran R Campbell, Adi Steif, Emma Laks, Hans Zahn, Daniel Lai, Andrew McPherson, Hossein Farahani, Farhia Kabeer, Ciara O'Flanagan, Justina Biele, Jazmine Brimhall, Beixi Wang, Pascale Walters; IMAXT Consortium; Alexandre Bouchard-Côté, Samuel Aparicio, Sohrab P Shah0

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.

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