starnet - Stacked Elastic Net

Implements stacked elastic net regression (Rauschenberger 2021 <doi:10.1093/bioinformatics/btaa535>). The elastic net generalises ridge and lasso regularisation (Zou 2005 <doi:10.1111/j.1467-9868.2005.00503.x>). Instead of fixing or tuning the mixing parameter alpha, we combine multiple alpha by stacked generalisation (Wolpert 1992 <doi:10.1016/S0893-6080(05)80023-1>).

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5.98 score 7 stars 1 dependents 9 scripts 440 downloads

palasso - Sparse Regression with Paired Covariates

Implements sparse regression with paired covariates (<doi:10.1007/s11634-019-00375-6>). The paired lasso is designed for settings where each covariate in one set forms a pair with a covariate in the other set (one-to-one correspondence). For the optional correlation shrinkage, install 'ashr' (<https://github.com/stephens999/ashr>) and 'CorShrink' (<https://github.com/kkdey/CorShrink>) from GitHub (see README).

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5.71 score 1 stars 6 dependents 19 scripts 307 downloads

cornet - Penalised Regression for Dichotomised Outcomes

Implements lasso and ridge regression for dichotomised outcomes (<doi:10.1080/02664763.2023.2233057>), i.e., numerical outcomes that were transformed to binary outcomes. Such artificial binary outcomes indicate whether an underlying measurement is greater than a threshold.

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5.67 score 2 stars 3 dependents 13 scripts 360 downloads

globalSeq - Global Test for Counts

The method may be conceptualised as a test of overall significance in regression analysis, where the response variable is overdispersed and the number of explanatory variables exceeds the sample size. Useful for testing for association between RNA-Seq and high-dimensional data.

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geneexpressionexonarraydifferentialexpressiongenomewideassociationtranscriptomicsdimensionreductionregressionsequencingwholegenomernaseqexomeseqmirnamultiplecomparison

5.32 score 1 stars 4 scripts 355 downloads

joinet - Penalised Multivariate Regression ('Multi-Target Learning')

Implements penalised multivariate regression (i.e., for multiple outcomes and many features) by stacked generalisation (<doi:10.1093/bioinformatics/btab576>). For positively correlated outcomes, a single multivariate regression is typically more predictive than multiple univariate regressions. Includes functions for model fitting, extracting coefficients, outcome prediction, and performance measurement. For optional comparisons, install 'remMap' from GitHub (<https://github.com/cran/remMap>).

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5.26 score 4 stars 1 dependents 8 scripts 301 downloads

semisup - Semi-Supervised Mixture Model

Implements a parametric semi-supervised mixture model. The permutation test detects markers with main or interactive effects, without distinguishing them. Possible applications include genome-wide association analysis and differential expression analysis.

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snpgenomicvariationsomaticmutationgeneticsclassificationclusteringdnaseqmicroarraymultiplecomparison

5.08 score 1 stars 4 scripts 358 downloads

sparselink - Sparse Regression for Related Problems

Estimates sparse regression models (i.e., with few non-zero coefficients) in high-dimensional multi-task learning and transfer learning settings, as proposed by Rauschenberger et al. (2025) <doi:10.1093/bioinformatics/btaf406>.

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4.70 score 1 stars 5 scripts 171 downloads

transreg - Penalised Regression with Multiple Sets of Prior Effects ('Transfer Learning')

Improves the predictive performance of ridge and lasso regression exploiting one or more sources of prior information on the importance and direction of effects (Rauschenberger and others 2023, <doi:10.1093/bioinformatics/btad680>). For running the vignette (optional), install 'fwelnet' and 'ecpc' from <https://github.com/kjytay/fwelnet> and <https://github.com/Mirrelijn/ecpc>, respectively.

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4.60 score 4 scripts 401 downloads