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Identification of somatic mutations in single cell DNA-seq using a spatial model of allelic imbalance

机译:使用等位性不平衡的空间模型鉴定单细胞DNA-SEQ中的细胞突变

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Recent advances in single cell technology have enabled dissection of cellular heterogeneity in great detail. However, analysis of single cell DNA sequencing data remains challenging due to bias and artifacts that arise during DNA extraction and whole-genome amplification, including allelic imbalance and dropout. Here, we present a framework for statistical estimation of allele-specific amplification imbalance at any given position in single cell whole-genome sequencing data by utilizing the allele frequencies of heterozygous single nucleotide polymorphisms in the neighborhood. The resulting allelic imbalance profile is critical for determining whether the variant allele fraction of an observed mutation is consistent with the expected fraction for a true variant. This method, implemented in SCAN-SNV (Single Cell ANalysis of SNVs), substantially improves the identification of somatic variants in single cells. Our allele balance framework is broadly applicable to genotype analysis of any variant type in any data that might exhibit allelic imbalance.
机译:单细胞技术的最新进展使得细细的细胞异质性能够进行解剖。然而,由于DNA提取和全基因组扩增期间出现的偏差和伪像,对单细胞DNA测序数据的分析保持挑战,包括等位基因不平衡和辍学。这里,我们通过利用邻域内的杂合单核苷酸多态性的等位基因频率,介绍了一种用于在单细胞全基因组序列测序数据中的任何给定位置的等位基因特异性扩增不平衡的框架。所得到的等位基因不平衡分布对于确定观察到的突变的变异等位基因部分是否与真正变体的预期级分一致。在SCAN-SNV中实现的该方法(SNV的单细胞分析),基本上改善了单细胞中体体变体的鉴定。我们的等位基因平衡框架广泛适用于任何可能表现出等位基因不平衡的任何数据中任何变体类型的基因型分析。

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