| Key OutputApp for results visualisation | TypeTool | DescriptionApp to easily visualise results from publication - Social inequalities in pregnancy metabolic profile | Access ShinyApp | ContactDr Ahmed Elhakeem, University of Bristol, email: a.elhakeem@bristol.ac.uk |
| Key OutputBayesian Life-course Structural Equation Models (BLSEM) | TypeModel | DescriptionTool for investigating causal linkages, mediation and pathways between exposures and health outcomes. | Access GitHub | ContactProfessor Marjo-Riitta Jarvin, Imperial College London, email: m.jarvelin@imperial.ac.uk |
| Key OutputBiological signatures of composite scores | TypeModel | DescriptionScript to decipher the specificity and justify the utility of established composite scores for cardiovascular risk. | AccessLink coming soon | ContactRin Wada, Imperial College London, email: rin.wada17@imperial.ac.uk |
| Key OutputComposite scores | TypeModel | DescriptionScript for generating the Biological Health Score (BHS), QRISK3, PCE, ideal cardiovascular health scores, diet score (DASH), physical activity score (MET). | AccessLink coming soon | ContactRin Wada, Imperial College London, email: rin.wada17@imperial.ac.uk |
| Key OutputCardiovascular health score generation | TypeModel | DescriptionSOP and script for generating the ideal cardiovascular health score in adults, relying on variables harmonised according to the LongITools protocol. | AccessLink coming soon | ContactBarbara Heude, Inserm, email:barbara.heude@inserm.fr |
| Key Outputfake: Flexible Data Simulation Using the Multivariate Normal Distribution | TypeModel | DescriptionThe R package fake (Flexible Data Simulation Using the Multivariate Normal Distribution) can be used to generate artificial data conditionally on pre-specified (simulated or user-defined) relationships between the variables and/or observations. Each observation is drawn from a multivariate Normal distribution where the mean vector and covariance matrix reflect the desired relationships. Outputs can be used to evaluate the performances of variable selection, graphical modelling, or clustering approaches by comparing the true and estimated structures. | AccessLink coming soon | ContactProfessor Marc Chadeau-Hyam, Imperial College London, email: m.chadeau@imperial.ac.uk |
| Key OutputModel age at adiposity peak and rebound | TypeModel | DescriptionScript for generating age and BMI at adiposity peak rebound, relying on variables harmonised according to the LongITools protocol. | AccessLink coming soon | ContactBarbara Heude, Inserm, email:barbara.heude@inserm.fr |
| Key OutputMsReg R scrip | TypeSoftware | DescriptionA DataShield compliant R script for consistent estimation of matched survey/cohort data. | AccessEmail contact | ContactAssociate Professor Andrea Piano Mortari, Tor Vergata University of Rome, email:andrea.pianomortari@uniroma2.eu |
| Key OutputMUVR2 | TypeMethod | DescriptionMultivariate methods with unbiased variable selection in R. A machine learning toolbox to associate predictor variables (e.g. Omics) to target variables (e.g. exposures or health outcomes). Performs PLS, random forest and elastic net modelling using nested cross-validation to minimise overfitting and false discovery. Performs unbiased selections of predictor variables-of-interest by incorporating variable selection procedures within the nested cross-validation. | Access Machine learning toolbox | ContactAssociate Professor Carl Brunius, Chalmers University, email: carl.brunius@chalmers.se |
| Key OutputOpenly available scripts from meta-analyses | TypeMethod | DescriptionFor some of the published meta-analyses, the analysis scripts have been made publicly available. These scripts can be used by other researchers for similar analyses. | AccessLocations, often a GitHub page or a supplement to the manuscript, are detailed in the published papers. Visit the Publications page on this website to find the meta-analyses. | ContactDr Janine Felix, Erasmus MC, email:j.felix@erasmusmc.nl |
| Key OutputStability Selection and Consensus Clustering in R: The R Package sharp | TypeModel | DescriptionThe R package sharp (Stability-enHanced Approaches using Resampling Procedures) provides an integrated framework for stability-enhanced variable selection, graphical modelling and clustering. In stability selection, a feature selection algorithm is combined with a resampling technique to estimate feature selection probabilities. The package offers flexibility in the modelling, includes diagnostic and visualisation tools, and allows for parallelisation. | Access Tools | ContactProfessor Marc Chadeau-Hyam, Imperial College London, email:m.chadeau@imperial.ac.uk |
| Key OutputSummary statistics from epigenome-wide association study meta-analyses | TypeOther | DescriptionDatasets containing the full results of published meta-analyses of epigenome-wide association studies of DNA methylation in relation to relevant phenotypes. These can be used by other researchers for further studies. | AccessOpen access locations (journal websites or central repositories) are detailed in the published papers. | ContactDr Janine Felix, Erasmus MC, email:j.felix@erasmusmc.nl |
| Key OutputTriplotGUI | TypeMethod | DescriptionA molecular epidemiology toolbox for investigating associations between exposures, omics and outcomes. | Access GitHub | ContactAssociate Professor Carl Brunius, Chalmers University, email: carl.brunius@chalmers.se |
