Covariance matrices play fundamental roles in myriad statistical procedures. When the observations in a dataset far outnumber the features, asymptotic theory and empirical evidence have demonstrated the sample covariance matrix to be the optimal estimator of this parameter. This assertion does not hold when the number of observations is commensurate with or smaller than the number of features. Consequently, statisticians have derived many novel covariance matrix estimators for the high-dimensional regime, often relying on additional assumptions about the parameter's structural characteristics (e.g., sparsity). While these estimators have greatly improved the ability to estimate covariance matrices in high-dimensional settings, objectively selecting the best estimator from among the many possible candidates remains a largely unaddressed challenge. The cvCovEst package addresses this methodological gap through its implementation of a cross-validated framework for covariance matrix estimator selection. This data-adaptive procedure's selections are asymptotically optimal under minimal assumptions -in fact, they are equivalent to the selections that would be made if given full knowledge of the true data-generating processes (i.e., an oracle selector) (van der Laan & Dudoit, 2003).
The immune system and placenta have a dynamic relationship across gestation to accommodate fetal growth and development. High-resolution characterization of this maternal-fetal interface is necessary to better understand the immunology of pregnancy and its complications. We developed a single-cell framework to simultaneously immuno-phenotype circulating, endovascular, and tissue-resident cells at the maternal-fetal interface throughout gestation, discriminating maternal and fetal contributions. Our data reveal distinct immune profiles across the endovascular and tissue compartments with tractable dynamics throughout gestation that respond to a systemic immune challenge in a gestationally-dependent manner. We uncover that mononuclear phagocytes and neutrophils drive the temporal immune composition of the placenta with remarkably diverse populations, including PD-L1-expressing subsets having compartmental and early gestational bias. Our approach and accompanying datasets provide a resource for additional investigations into gestational immunology and evoke a more significant role for the innate immune system in establishing the microenvironment of early pregnancy.
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