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  "Title": "Covariance-Aware Deconvolution of Bulk Transcriptomic Samples",
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  "Description": "Estimates cell-type proportions in bulk transcriptomic\nsamples with a probabilistic convolution model that integrates\nthe gene-gene covariance structure of purified reference\nprofiles. Cellular ratios are recovered by maximum likelihood\nunder a multivariate Gaussian convolution, using analytic\ngradients and Hessians, an isometric log-ratio\nreparametrisation (Helmert basis) that enforces the simplex\nconstraint, and Marquardt-Levenberg or Newton-type optimisers.\nThe methodology is described in Chassagnol, Nuel and Becht\n(2023) <doi:10.48550/arXiv.2309.09557>.",
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  "Date/Publication": "2026-10-16 15:12:25 UTC",
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        "Log-likelihood along the simplex",
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