Journal
BIOINFORMATICS
Volume 27, Issue 4, Pages 587-588Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btq684
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Funding
- Medical Research Council Clinical Sciences Centre
- Nouvelle Societe Francaise d'Atherosclerose
- EU Community [226756, HEALTH-F4-2010-241504]
- PHC ALLIANCE [19419PH]
- Wellcome Trust
- MRC [G0600609]
- Biotechnology and Biological Sciences Research Council [BB/C519670/1] Funding Source: researchfish
- Medical Research Council [G0801056B, G0600609, MC_U120097112] Funding Source: researchfish
- MRC [MC_U120097112, G0600609] Funding Source: UKRI
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ESS++ is a C++ implementation of a fully Bayesian variable selection approach for single and multiple response linear regression. ESS++ works well both when the number of observations is larger than the number of predictors and in the 'large p, small n' case. In the current version, ESS++ can handle several hundred observations, thousands of predictors and a few responses simultaneously. The core engine of ESS++ for the selection of relevant predictors is based on Evolutionary Monte Carlo. Our implementation is open source, allowing community-based alterations and improvements.
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