National Frontier Center of Disease Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
School of Mathematics and Statistics, Key Laboratory for Applied Statistics of the Ministry of Education, Northeast Normal University, 130024, Changchun, China.
Nucleic Acids Res. 2021 Jun 4;49(10):e57. doi: 10.1093/nar/gkab106.
Single-nucleotide variant (SNV) detection in the genome of single cells is affected by DNA amplification artefacts, including imbalanced alleles and early PCR errors. Existing single-cell genotyper accuracy often depends on the quality and coordination of both the target single-cell and external data, such as heterozygous profiles determined by bulk data. In most single-cell studies, information from different sources is not perfectly matched. High-accuracy SNV detection with a limited single data source remains a challenge. We developed a new variant detection method, SCOUT (Single Cell Genotyper Utilizing Information from Local Genome Territory), the greatest advantage of which is not requiring external data while base calling. By leveraging base count information from the adjacent genomic region, SCOUT classifies all candidate SNVs into homozygous, heterozygous, intermediate and low major allele SNVs according to the highest likelihood score. Compared with other genotypers, SCOUT improves the variant detection performance by 2.0-77.5% in real and simulated single-cell datasets. Furthermore, the running time of SCOUT increases linearly with sequence length; as a result, it shows 400% average acceleration in operating efficiency compared with other methods.
单细胞基因组中单核苷酸变异 (SNV) 的检测受到 DNA 扩增伪影的影响，包括不平衡等位基因和早期 PCR 错误。现有的单细胞基因型检测准确性通常取决于目标单细胞和外部数据（如由批量数据确定的杂合子谱）的质量和协调性。在大多数单细胞研究中，不同来源的信息并不完全匹配。利用有限的单个数据源进行高精度 SNV 检测仍然是一个挑战。我们开发了一种新的变异检测方法，SCOUT（利用局部基因组区域信息的单细胞基因型检测），其最大的优势是在碱基调用时不需要外部数据。通过利用相邻基因组区域的碱基计数信息，SCOUT 根据最高似然评分将所有候选 SNV 分类为纯合子、杂合子、中间和低主要等位基因 SNV。与其他基因型检测方法相比，SCOUT 在真实和模拟的单细胞数据集的变异检测性能提高了 2.0-77.5%。此外，SCOUT 的运行时间随序列长度呈线性增加；因此，与其他方法相比，其平均运行效率提高了 400%。
