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Abstract:
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Problems in genome sequencing and single cell analysis have spurred developments of Statistical methods and theory for over two decades. In particular, many new statistical models and methods have been inspired by the problem of DNA copy number analysis in bulk tissues. Here, we will present new challenges and opportunities in DNA copy number analysis brought on by the latest technologies in single cell genomics. We will show the latest findings in this area made possible by the marriage of leading-edge technologies and new statistical models.
We focus on cancer genomes, aiming to disentangle to contributions of somatic copy number aberrations and chromatin remodeling in shaping the clonal diversity of cancers. We present Alleloscope, a method for allele-specific copy number estimation that can be applied to single cell DNA and ATAC sequencing data, either separately or in combination. This approach allows for integrative multi-omic analysis of allele-specific copy number and chromatin accessibility on the same cell. We analyze single cell data from gastric, colorectal, and breast cancer samples, with extensive validation using matched linked-read sequencing.
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