Putri W Novianti1,2, Barbara C Snoek2, Saskia M Wilting2, Mark A van de Wiel1,3. 1. Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. 2. Department of Pathology, VU University Medical Center, Amsterdam, The Netherlands. 3. Department of Mathematics, VU University, Amsterdam, The Netherlands.
Abstract
SUMMARY: Our aim is to improve omics based prediction and feature selection using multiple sources of auxiliary information: co-data. Adaptive group regularized ridge regression (GRridge) was proposed to achieve this by estimating additional group-based penalty parameters through an empirical Bayes method at a low computational cost. We illustrate the GRridge method and software on RNA sequencing datasets. The method boosts the performance of an ordinary ridge regression and outperforms other classifiers. Post-hoc feature selection maintains the predictive ability of the classifier with far fewer markers. AVAILABILITY AND IMPLEMENTATION: GRridge is an R package that includes a vignette. It is freely available at ( https://bioconductor.org/packages/GRridge/ ). All information and R scripts used in this study, including those on retrieval and processing of the co-data, are available from http://github.com/markvdwiel/GRridgeCodata . CONTACT: mark.vdwiel@vumc.nl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
SUMMARY: Our aim is to improve omics based prediction and feature selection using multiple sources of auxiliary information: co-data. Adaptive group regularized ridge regression (GRridge) was proposed to achieve this by estimating additional group-based penalty parameters through an empirical Bayes method at a low computational cost. We illustrate the GRridge method and software on RNA sequencing datasets. The method boosts the performance of an ordinary ridge regression and outperforms other classifiers. Post-hoc feature selection maintains the predictive ability of the classifier with far fewer markers. AVAILABILITY AND IMPLEMENTATION: GRridge is an R package that includes a vignette. It is freely available at ( https://bioconductor.org/packages/GRridge/ ). All information and R scripts used in this study, including those on retrieval and processing of the co-data, are available from http://github.com/markvdwiel/GRridgeCodata . CONTACT: mark.vdwiel@vumc.nl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Wina Verlaat; Barbara C Snoek; Daniëlle A M Heideman; Saskia M Wilting; Peter J F Snijders; Putri W Novianti; Annina P van Splunter; Carel F W Peeters; Nienke E van Trommel; Leon F A G Massuger; Ruud L M Bekkers; Willem J G Melchers; Folkert J van Kemenade; Johannes Berkhof; Mark A van de Wiel; Chris J L M Meijer; Renske D M Steenbergen Journal: Clin Cancer Res Date: 2018-04-09 Impact factor: 12.531
Authors: Inge van den Berg; Marcel Smid; Robert R J Coebergh van den Braak; Mark A van de Wiel; Carolien H M van Deurzen; Vanja de Weerd; John W M Martens; Jan N M IJzermans; Saskia M Wilting Journal: Mol Oncol Date: 2021-09-30 Impact factor: 6.603
Authors: Iris Babion; Barbara C Snoek; Putri W Novianti; Annelieke Jaspers; Nienke van Trommel; Daniëlle A M Heideman; Chris J L M Meijer; Peter J F Snijders; Renske D M Steenbergen; Saskia M Wilting Journal: Clin Epigenetics Date: 2018-06-07 Impact factor: 6.551