Sharon M. Lutz

Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care

Current Appointment

Assistant Professor
Department of Population Medicine
Harvard Medical School and Harvard Pilgrim Health Care

Research Interests

Statistical genetics and genomics including high-dimensional statistics, computational statistics, and mediation analysis

Publications

Publications can be found on Google Scholar.

Software

reverseDirection

An R package that examines the ability to use MR to infer the effect direction. On GitHub and implements the method from the following paper:

reverseMA

An R package that examines mediation analysis in the presence of reverse causality. On GitHub and implements the method from the following paper:

RNAseqRare

An R package that examines expression quantitative trait loci (eQTL) analyses of rare variants for RNA-seq data. On GitHub and implements the method from the following paper:

ePowerLI

An R package that performs an empirical power analysis of the interaction of two normally distributed traits in longitudinal unbalanced datasets. On GitHub and implements the power analysis used in the following paper:

gxeRC

An R package that examines SNP by environment interactions for both common and rare variants. On GitHub and implements the power analysis used in the following paper:

Umediation

An R package that examines the role of unmeasured confounding of the exposure-mediator-outcome relationship in mediation analysis. On GitHub and implements the method from the following paper:

pleiotropy

An R package that tests for common and rare variant associations with multiple phenotypes using the Hausdorff metric in a permutation based framework. On GitHub and implements the method from the following paper:

SecondaryPhenotype

An R package that adjusts for ascertainment bias when testing for genetic associations of secondary phenotypes in population based studies. On GitHub and implements the method from the following paper:

NPBAT

An interactive software package for the analysis of population based genetic association studies. On Google Sites and implements the method from the following paper:

CausalScreen

An R package that implements a screening step to increase power when testing for direct genetic effects of multiple SNPs in family based association studies using causal inference methodology. On GitHub and implements the methods from the following papers:

bayesIndirect

An R package that examines the indirect effect of a SNP on the outcome through the mediator in a Bayesian framework with a spike and slab prior. On GitHub and implements the method from the following paper:

snpDRAC

An R package that examines power to detect a genetic association for dominant, recessive, additive, and co-dominant models. This R package was built as a learning tool for BST 227: Introduction to Statistical Genetics on GitHub.