Lisa Strug

Professor

University of Toronto

Canada

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About

Lisa Strug is a Professor at the University of Toronto, Canada. Her research areas encompass genetic association analysis using long-read sequencing data, multi-omics data integration, and differential gene expression analysis. She has contributed significantly to the understanding of cystic fibrosis and its related disorders, along with advancements in methodologies for analyzing complex genetic data. Additionally, she has worked on protocols for improving patient management in the context of COVID-19.

Articles (12)

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2025

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2024

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2023

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2022

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2022

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2022

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2021

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2021

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2021

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2021

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2021

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2021

Collaborators (3)

Donald Black

Professor

The University of Iowa Roy J and Lucille A Carver College of Medicine

UNITED STATES

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Jüri Reimand

Associate professor

University of Toronto

CANADA

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Ning Shang

Columbia University

UNITED STATES

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Lisa Strug

Research Interests

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Articles (12)

On the analysis of genetic association with long-read sequencing data

Directional integration and pathway enrichment analysis for multi-omics data

RoPE: A robust profile likelihood method for differential gene expression analysis

Expression of cystic fibrosis lung disease modifier genes in human airway models

Leveraging TOPMed imputation server and constructing a cohort-specific imputation reference panel to enhance genotype imputation among cystic fibrosis patients

A flexible summary statistics-based colocalization method with application to the mucin cystic fibrosis lung disease modifier locus

Genome-wide association study of pediatric obsessive-compulsive traits: shared genetic risk between traits and disorder

Rare loss-of-function variants in type I IFN immunity genes are not associated with severe COVID-19

649: Pharmacologic response of rare CFTR folding variants is mediated by a silent polymorphism that alters ribosome velocity

Correction to: Cystic fibrosis–related diabetes onset can be predicted using biomarkers measured at birth

The X factor: A robust and powerful approach to X‐chromosome‐inclusive whole‐genome association studies

Implementation of serological and molecular tools to inform COVID-19 patient management: protocol for the GENCOV prospective cohort study

Collaborators (3)

Donald Black

Jüri Reimand

Ning Shang

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