Statistical genetics is undergoing the same transition to big data that all branches of applied statistics are experiencing. With the advent of inexpensive DNA sequencing, the transition is only accelerating. This brief review highlights some modern techniques with recent successes in statistical genetics. These include: (a) lasso penalized regression and association mapping, (b) ethnic admixture estimation, (c) matrix completion for genotype and sequence data, (d) the fused lasso and copy number variation, (e) haplotyping, (f) estimation of relatedness, (g) variance components models, and (h) rare variant testing. For more than a century, genetics has been both a driver and beneficiary of statistical theory and practice. This symbiotic relationship will persist for the foreseeable future.

中文翻译：

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下一代统计遗传学：高维数据中的建模、惩罚和优化。

统计遗传学正在经历与应用统计的所有分支正在经历的相同的大数据过渡。随着廉价 DNA 测序的出现，这种转变只会加速。这篇简短的评论重点介绍了最近在统计遗传学方面取得成功的一些现代技术。这些包括：（a）套索惩罚回归和关联映射，（b）种族混合估计，（c）基因型和序列数据的矩阵完成，（d）融合套索和拷贝数变异，（e）单倍型，（f）相关性估计、(g) 方差分量模型和 (h) 稀有变异测试。一个多世纪以来，遗传学一直是统计理论和实践的推动者和受益者。在可预见的未来，这种共生关系将持续下去。