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Xihong Lin

Researcher at Harvard University

Publications -  389
Citations -  32083

Xihong Lin is an academic researcher from Harvard University. The author has contributed to research in topics: Population & Genome-wide association study. The author has an hindex of 76, co-authored 361 publications receiving 26162 citations. Previous affiliations of Xihong Lin include Texas A&M University & University of Washington.

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Journal Article

Quantifying pql bias in estimating cluster-level covariate effects in generalized linear mixed models for group-randomized trials

TL;DR: In this article, the asymptotic bias and variance of the penalized quasilike-lihood (PQL) estimator of the cluster-level covariate eect in generalized linear mixed models for group-randomized trials where the number of clusters n is small and the cluster size m is large were derived.
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A population pharmacokinetic model with time-dependent covariates measured with errors.

TL;DR: A population pharmacokinetic (PK) model with time-dependent covariates measured with errors is used to model S-oxybutynin's kinetics following an oral administration of Ditropan, and allows the distribution rate to depend on time- dependent covariates blood pressure and heart rate.
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Quantitative quality-assessment techniques to compare fractionation and depletion methods in SELDI-TOF mass spectrometry experiments

TL;DR: The peaks detected using the unfractionated plasma samples have the highest reproducibility as determined by the reliability ratio, and the use of the Sigma multi-removal kit does not improve peak detection.
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Powerful gene set analysis in GWAS with the Generalized Berk-Jones statistic

TL;DR: The Generalized Berk-Jones (GBJ) statistic is introduced for GSA, a permutation-free parametric framework that offers asymptotic power guarantees in certain set-based testing settings and a GBJ step-down inference technique that can discriminate between gene sets driven to significance by single genes and those demonstrating group-level effects.
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Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer

TL;DR: This paper performed cross-ancestry genome-wide association studies in European, East Asian and African populations to identify new susceptibility loci to lung cancer among diverse populations, and discovered five loci that have not been previously reported.