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Abstract:
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Lineage tracing provides key insights into the fates of individual cells in complex tissues. Recent statistical methods developed for lineage reconstruction based on expression data are suitable for short time frames, while lineage tracing based on more stable genetic markers is needed for studies that span time scales over months or years. However, variant calling from single cell sequencing suffers from “genetic drop-out”, including low coverage and allelic bias. To address these issues, we developed SClineager, a Bayesian Hierarchical model, to perform single cell lineage tracing based on single cell sequencing-derived variants and with correction of genetic dropouts. We systematically validated SClineager on a series of single cell sequencing datasets. Our analyses showed the improvement our approach provided for both inter- and intra-patient lineage tracing. We discovered genetic shifting and accumulation of variants in single tumor and non-tumor cells that cannot be revealed by expression-based analyses.
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