QSU Tools and Resources
Tools and Resources Developed by QSU Members
- Desai Lab and QSU
- SimTimeVar: Simulate Longitudinal Dataset with Time-Varying Correlated Covariates
- Stratamatch: Stratification and Matching for Large Observational Data Sets
- ShinyApp: A comprehensive health-risk prediction tool for postmenopause women
- ShinyApp: Random Forest Model for Optimizing Individualized Blood Pressure Management
- Website: COVID Endpoint Registry
- Gentles Lab
- PRECOG: Prediction of Clinical Outcomes from Genomic Profiles
- TMIs: Tumor Microenvironment Interactomes (TMIs)
- Han Lab
- SPLC-RAT: Second Primary Lung Cancer-Risk Assessment Tool
- He Lab
- Knockoffscreen: Identification of Putative Causal Loci in Whole-Genome Sequencing Data via Knockoff Statistics
- LGRF: for the Longitudinal Genetic Random Field model (LGRF) to test the association between a longitudinally measured quantitative outcome and a set of genetic variants in a gene/region
- LGWEIS: for longitudinal gene-environment-wide interaction studies
- FST Package: for unified sequence-based association tests allowing for multiple functional annotation scores
- GenoNet: Web interfance for predicting cell type specific functional consequences of non-coding variation across 127 tissues/cell types. http://www.funlda.com/genonet
- Mathur Lab
- PublicationBias: Conducts sensitivity analysis for publicaiton bias in meta-analysis
- MtaUtility: Contains functions to estimate the proportion of effects stronger than a threshold of scientifc importance, to make various effect size converions, and to compute and format inference in a meta-analysis
- Regmedint: Conducts regression-based causal mediation analysis
- NRejections: Computes metrics of outcome-wide evidence strength for studies testing multiple correlated outcomes
- EValue: Conducts sensitivity analyses for unmeasured confounding or selection of bias in observational studies and meta-analysis
- Replicate: Conducts satistical analyses for multisite replication projects
- Qualtrics Mousetracker: Software in R, Javascript, and Qualtrics to design and analyze psychology experiments that use fine-grained mouse-tracking measures of perceptual category competition
- EVALUE: Calculates the E-value, a measure of sensitivity to unmeasured confounding
- Website: E-value Calculator