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We propose an estimation procedure for covariation in wide compositional datasets. For compositions, widely-used logratio variables are interdependent dueto a common reference. Logratio uncorrelated compositions are linearlyindependent before the unit-sum constraint is imposed. We show how they areused to construct bespoke shrinkage targets for logratio covariance matricesand test a simple procedure for partial correlation estimates on both asimulated and a single-cell gene expression data set. For the underlyingcounts, different zero imputations are evaluated. The partial correlationinduced by the closure is derived analytically. Data and code are availablefrom GitHub.

Compositional Covariance Shrinkage and Regularised Partial Correlations