Semi-Supervised Deconvolution of Bulk RNA-Seq Data with Hyperparameter Optimization R package dicepro version 1.0.2 Performs semi-supervised deconvolution of bulk RNA sequencing (RNA-seq) data. Known cell-type proportions are estimated using supervised methods -- 'CIBERSORTx' (CSx), 'CIBERSORT' (CS), 'FARDEEP' (Fast And Robust DEconvolution of Expression Profiles), and 'DCQ' (Digital Cell Quantifier) -- while unknown components are inferred using non-negative matrix factorization ('NMF') with limited-memory Broyden-Fletcher-Goldfarb-Shanno with bounds ('L-BFGS-B') optimization. Hyperparameters are selected automatically using a Pareto-frontier-based approach with knee-point detection, allowing application when the reference signature matrix is incomplete. More details about 'DICEpro' can be found in Ba et al. (2026) <doi:10.64898/2026.06.17.732876>. Software Depends: R (>= 4.1.0) Imports: Rcpp (>= 1.0.12), lbfgsb3c, KraljicMatrix, ggplot2, patchwork, FARDEEP, ComICS, lme4, e1071, preprocessCore, parallel LinkingTo: Rcpp (>= 1.0.12), RcppEigen Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Kalidou BA <sistm.soft.maintain@gmail.com> Comprehensive R Archive Network (CRAN) Kalidou BA [aut, cre], Boris P. Hejblum [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=dicepro/LICENSE) 2026-06-30 application/tgz https://CRAN.R-project.org/package=dicepro doi:10.32614/CRAN.package.dicepro