Sengupta Dhriti, Botha Gerrit, Meintjes Ayton, Mbiyavanga Mamana, Hazelhurst Scott, Mulder Nicola, Ramsay Michèle, Choudhury Ananyo
Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Computational Biology Division, Department of Integrative Biomedical Sciences, Institute for Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.
Cell Genom. 2023 May 23;3(6):100332. doi: 10.1016/j.xgen.2023.100332. eCollection 2023 Jun 14.
Based on evaluations of imputation performed on a genotype dataset consisting of about 11,000 sub-Saharan African (SSA) participants, we show Trans-Omics for Precision Medicine (TOPMed) and the African Genome Resource (AGR) to be currently the best panels for imputing SSA datasets. We report notable differences in the number of single-nucleotide polymorphisms (SNPs) that are imputed by different panels in datasets from East, West, and South Africa. Comparisons with a subset of 95 SSA high-coverage whole-genome sequences (WGSs) show that despite being about 20-fold smaller, the AGR imputed dataset has higher concordance with the WGSs. Moreover, the level of concordance between imputed and WGS datasets was strongly influenced by the extent of Khoe-San ancestry in a genome, highlighting the need for integration of not only geographically but also ancestrally diverse WGS data in reference panels for further improvement in imputation of SSA datasets. Approaches that integrate imputed data from different panels could also lead to better imputation.
基于对一个由约11000名撒哈拉以南非洲（SSA）参与者组成的基因型数据集进行的插补评估，我们发现精准医学跨组学（TOPMed）和非洲基因组资源（AGR）目前是插补SSA数据集的最佳面板。我们报告了在来自东非、西非和南非的数据集中，不同面板插补的单核苷酸多态性（SNP）数量存在显著差异。与95个SSA高覆盖全基因组序列（WGS）的子集进行比较表明，尽管AGR插补数据集小约20倍，但与WGS的一致性更高。此外，插补数据集与WGS数据集之间的一致性水平受到基因组中科伊桑祖先程度的强烈影响，这突出表明不仅需要在参考面板中整合地理上不同的WGS数据，还需要整合祖先上不同的WGS数据，以进一步改进SSA数据集的插补。整合来自不同面板的插补数据的方法也可能导致更好的插补。
