Xiaoquan Wen

Professor

University of Michigan

United States

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Professor Xiaoquan Wen is a faculty member at the University of Michigan, USA. His research focuses on gene identification methods, high-throughput experiments, and the transcriptional responses of the immune system. Recent publications include studies on genetic control at single-cell resolution and the integration of functional annotations to enhance gene-based association analysis. His work aims to advance understanding of complex traits and molecular mechanisms in various biological contexts.

Articles (11)

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2024

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2023

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2023

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2023

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2023

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2021

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2021

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2020

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2020

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2020

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2020

Collaborators (4)

Heather Wheeler

Associate Professor

Loyola University Chicago

UNITED STATES

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Alvaro Barbeira

University of Chicago

UNITED STATES

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Jean Morrison

Assistant Professor

University of Michigan

UNITED STATES

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Milton Pividori

Assistant Professor

University of Colorado Anschutz Medical Campus

UNITED STATES

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Xiaoquan Wen

Research Interests

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Articles (11)

Imperfect gold standard gene sets yield inaccurate evaluation of causal gene identification methods

JUMP: replicability analysis of high-throughput experiments with applications to spatial transcriptomic studies

Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single-cell resolution

Analysis of transcriptional changes in the immune system associated with pubertal development in a longitudinal cohort of children with asthma

Probabilistic integration of transcriptome-wide association studies and colocalization analysis identifies key molecular pathways of complex traits

Revisiting the genome-wide significance threshold for common variant GWAS

Probabilistic colocalization of genetic variants from complex and molecular traits: promise and limitations

Fine‐mapping and QTL tissue‐sharing information improves the reliability of causal gene identification

Integrating comprehensive functional annotations to boost power and accuracy in gene-based association analysis

Quantify and control reproducibility in high-throughput experiments

PTWAS: investigating tissue-relevant causal molecular mechanisms of complex traits using probabilistic TWAS analysis

Collaborators (4)

Heather Wheeler

Alvaro Barbeira

Jean Morrison

Milton Pividori

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