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American Journal of Human Genetics|January 21, 2026
A gene-specific variance-control approach corrects polygenicity-driven inflation observed in transcriptome-wide association studiesYanyu Liang, Festus Nyasimi, Hae Kyung ImBiorxiv : the Preprint Server for Biology|October 31, 2023
Pervasive polygenicity of complex traits inflates false positive rates in transcriptome-wide association studiesYanyu Liang, Festus Nyasimi, Hae Kyung ImDevelopmental Cognitive Neuroscience|March 18, 2025
BrainXcan identifies brain features associated with behavioral and psychiatric traits using large-scale genetic and imaging dataYanyu Liang, Festus Nyasimi, Owen Melia, et al.Nature Communications|March 4, 2021
A scalable unified framework of total and allele-specific counts for cis-QTL, fine-mapping, and predictionYanyu Liang, François Aguet, Alvaro N Barbeira, et al.Genome Biology|January 14, 2022
Polygenic transcriptome risk scores (PTRS) can improve portability of polygenic risk scores across ancestriesYanyu Liang, Milton Pividori, Ani Manichaikul, et al.Biorxiv : the Preprint Server for Biology|November 28, 2024
scPrediXcan integrates advances in deep learning and single-cell data into a powerful cell-type-specific transcriptome-wide association study frameworkYichao Zhou, Temidayo Adeluwa, Lisha Zhu, et al.STAR Protocols|February 14, 2026
Protocol to perform cell-type-specific transcriptome-wide association study using scPrediXcan frameworkYichao Zhou, Sarah Sumner, Temidayo Adeluwa, et al.Cell Genomics|May 15, 2025
scPrediXcan integrates deep learning methods and single-cell data into a cell-type-specific transcriptome-wide association study frameworkYichao Zhou, Temidayo Adeluwa, Lisha Zhu, et al.Bioinformatics (Oxford, England)|November 6, 2018
ukbREST: efficient and streamlined data access for reproducible research in large biobanksMilton Pividori, Hae Kyung ImPageof 14