Code for analysis of metabolomics data for DMD natural history study

GENEPARK is a large study that aimed for finding blood-based biomarkers Parkinson's disease. Here we provide the R code for reproducing the main results of the project.

Mendelian Randomization with Biomarker Associations for Causality with Outcomes

Fit Poolwise Regression Models

Omics BioAnalytics - RShiny web app for bioinformatics analyses

Code and data to support doi:10.1136/jitc-2020-001506

Source code for "Overexpression of CRNDE in glioblastoma is a poor survival prognosis biomarker" paper

🔎 Web-based Tool for Interacting with FOBI Ontology

Predicting eczema severity with biomarkers using a Bayesian state-space model

Gene Polymorphisms Among Plasmodium vivax Geographical Isolates and the Potential as New Biomarkers for Gametocyte Detection

Incidence Estimation Tools

Ensemble Model Biomarker Analysis R package

A comprehensive R package for label-free proteomics data analysis and modeling

R package for cleaning biomarker test results in EHR (especially CPRD Aurum)

R Code and website for Longitudinal Fecal Calprotectin Profiles Characterize Disease Course Heterogeneity in Crohn’s Disease by Constantine-Cooke et al.

CimpleG, an R package to find (small) CpG signatures.

This package contains a Rshiny webtool developed to allow the calculation of the metabolic predictors developed by the groups of MOLEPI and LCBC (LUMC), from raw Nightingale Health 1H-NMR metabolomics data.

Univariate conditional average treatment effect estimation for predictive biomarker discovery

R package BioPred

OmicSelector - Environment, docker-based application and R package for biomarker signiture selection (feature selection) & deep learning diagnostic tool development from high-throughput high-throughput omics experiments and other multidimensional datasets. Initially developed for miRNA-seq, RNA-seq and qPCR.