规范化(社会学)
范围(计算机科学)
DNA测序
单细胞测序
模棱两可
生物
计算生物学
拷贝数变化
DNA
人口
癌症基因组测序
基因组
计算机科学
遗传学
参考基因组
外显子组测序
基因
突变
人口学
社会学
人类学
程序设计语言
出处
期刊:Methods in molecular biology
日期:2022-01-01
卷期号:: 279-288
标识
DOI:10.1007/978-1-0716-2293-3_18
摘要
AbstractWhole-genome single-cell DNA sequencing (scDNA-seq) enables the characterization of copy number profiles at the cellular level. This circumvents the averaging effects associated with bulk-tissue sequencing and has increased resolution yet decreased ambiguity in deconvolving cancer subclones and elucidating cancer evolutionary history. ScDNA-seq data is, however, sparse, noisy, and highly variable even within a homogeneous cell population, due to the biases and artifacts that are introduced during the library preparation and sequencing procedure. Here, we describe SCOPE, a normalization and copy number estimation method for scDNA-seq data. We give an overview of the methodology and illustrate SCOPE with step-by-step demonstrations.Key wordsSingle-cell DNA sequencingCopy number variationData normalizationSegmentationLatent factor
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