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DeCovarT
2.3.1
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Functions
Vignettes
External resources
Manuscript, preprint & seminar slides
Prepare inputs
In silico GRN inference
Feature selection for reference-based deconvolution
Mathematical and programmatic introduction to DeCovarT
How to build synthetic scenarios (means, covariance, ADEMP)
Distances, overlap, and covariance information
Paper: numerical simulation study
§ 2.1 · Bivariate toy (J = 2, G = 2)
§ 2.2 · Covariance-driven hybrid (J = 3, G = 20)
DeCovarT mathematical appendix
MLE properties and asymptotic inference
DeCovarT perspectives: OLS, Bayesian, quasi-likelihood, and more
Single-cell to bulk alignment: cell counts, averages, compositions
Supplementary simulation appendix
App. S1 · Regular-case MLE and identifiability
App. S2 · Covariance inversion strategies
App. S3 · Solver scalability
App. S4 · Covariance modelling assumptions
App. S5 · Model mis-specification (outlook)
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YEAR: 2026 COPYRIGHT HOLDER: Bastien Chassagnol
