Expression reflects population structure
Expression reflects population structure
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DOI：
10.1371/journal.pgen.1007841
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发表时间：
2018-12-01
期刊：
影响因子：
4.5
通讯作者：
Pachter, Lior
中科院分区：
文献类型：
--
作者：
Brown, Brielin C.;Bray, Nicolas L.;Pachter, Lior
基因型数据中的群体结构已被广泛研究，并通过查看基因型矩阵的主成分来揭示。然而，没有类似的基因表达数据中的群体结构的分析已经进行，部分原因是基因表达矩阵的朴素主成分分析不按群体聚类。我们确定了一个线性投影，揭示了基因表达数据中的群体结构。我们的方法依赖于通过典型相关分析的基因型的主成分的基因表达的主成分的耦合。我们的方法能够确定由每个基因解释的典型相关投影中的方差的显著性。我们确定了3，571个显著基因，其中只有837个先前报道在GEUVADIS结果中具有相关的eQTL。我们表明，我们的预测主要不是由已知顺式eQTL的等位基因频率差异驱动的，并且仅使用几百个随机选择的基因和SNP就可以恢复类似的预测。最后，我们提出了初步工作的后果eQTL分析。我们观察到，使用我们的投影坐标作为协变量的结果，在发现略少的基因与eQTL，但这些基因在GTEx匹配的组织中以略高的速率复制。
Population structure in genotype data has been extensively studied, and is revealed by looking at the principal components of the genotype matrix. However, no similar analysis of population structure in gene expression data has been conducted, in part because a naive principal components analysis of the gene expression matrix does not cluster by population. We identify a linear projection that reveals population structure in gene expression data. Our approach relies on the coupling of the principal components of genotype to the principal components of gene expression via canonical correlation analysis. Our method is able to determine the significance of the variance in the canonical correlation projection explained by each gene. We identify 3,571 significant genes, only 837 of which had been previously reported to have an associated eQTL in the GEUVADIS results. We show that our projections are not primarily driven by differences in allele frequency at known cis-eQTLs and that similar projections can be recovered using only several hundred randomly selected genes and SNPs. Finally, we present preliminary work on the consequences for eQTL analysis. We observe that using our projection co-ordinates as covariates results in the discovery of slightly fewer genes with eQTLs, but that these genes replicate in GTEx matched tissue at a slightly higher rate.