DeCovarT
Overview
DeCovarT is an R package for bulk transcriptomic deconvolution that accounts
for gene–gene covariance in purified reference populations. Bulk observations
are modelled as Gaussian convolutions of cell-type means and covariances, with
cellular proportions recovered on the open simplex via an unconstrained
(additive logistic) parametrisation.
The main entry point is deconvolute_ratios(), which runs one or more solvers
in parallel and returns estimated proportions plus optional benchmark metrics.
Seminar slides (iframe)
Doctorants seminar overview (Quarto reveal.js). Prefer
full screen
when presenting.
Pipeline Architecture
%%{init: {"theme": "sandstone"}}%%
flowchart TD
A["Bulk RNA-seq mixture<br/>Genes × Samples"] --> C["Gene intersection,<br/>optional scaling"]
B["Cell-type reference<br/>Means μ_j + covariances Σ_j"] --> C
C --> D["deconvolute_ratios()<br/>Parallel solvers"]
D --> E["DeCovarT<br/>Covariance-aware MLE<br/>ALR + marqLevAlg"]
D --> F["First-generation methods<br/>NNLS · QP · GLS · rlm · ν-SVR"]
E --> G["Proportion estimates<br/>on the simplex"]
F --> G
G --> H["Optional benchmark metrics<br/>vs true ratios"]
G --> I["Correlation heatmaps<br/>and visualisation"]
H --> J["Comparative evaluation"]
I --> J
The diagram above summarises the end-to-end workflow.
This package combines Gaussian mixture convolution modelling, simplex
reparametrisation (ALR / soft-max), analytic likelihood derivatives, and
classical linear deconvolution baselines on bulk transcriptomic mixtures.
Solver outputs remain method-specific; shared evaluation uses standardised
proportion tables and optional ground-truth ratios from simulations.
Interactive package structure
Three graphs, regenerated with
Rscript scripts/visualisation/generate_package_network_functions.R.
The estimation and interval network
is the Gaussian-convolution fit. The
simulation and benchmark network
is the scenario generator and the ADEMP summaries. The
visualisation network
covers the Monte Carlo plots.
Built-in deconvolution algorithms
| Algorithm | Interface | Notes / upstream |
|---|
| DeCovarT (Marquardt–Levenberg) | deconvolute_ratios_Marquardt_Levenberg | Covariance-aware MLE |
| Non-negative least squares | deconvolute_ratios_nnls | Lawson–Hanson NNLS |
| DeconRNASeq-style QP | deconvolute_ratios_deconrnaseq | Simplex QP via {limSolve} |
Robust linear model (rlm) | deconvolute_ratios_rlm | ABIS / Monaco-style RLR |
| CIBERSORT-style $\nu$-SVR | deconvolute_ratios_cibersort | Linear-kernel SVR via {e1071} |
All of the above ship with the package (no extra method packages required).
Links to the paper
Installation
Once the package is on CRAN:
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