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Open access Jul 2026

CIT-Lasso: a scalable approach beyond guilty by association for identifying causal variants from genome-wide summary statistics

We present CIT-Lasso, a framework that uses only summary statistics to identify, genome-wide, sets of variants carrying non-redundant information on a phenotype, distinguishing likely causal variants from correlated variants that are merely associated. The open-source implementation completes genome-wide analysis in un...

Zihuai He, Benjamin B. Chu, James Yang et al. · 0 citations
Open access Aug 2026

Robust Inference With Ghostknockoffs in Genome‐Wide Association Studies With Sample Relatedness

Genome‐wide association studies (GWASs) have been extensively adopted to depict the underlying genetic architecture of complex traits. Recent studies show that knockoff‐based methods can identify variants with unique, potentially causal effects on phenotypes. However, their statistical validity and effectiveness in stu...

Xinran Qi, M. Belloy, Jiaqi Gu et al. · 0 citations

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