Peilin Jia

This paper evaluates polygenic and methylation risk scores for predicting overweight-related hypertension in Chinese populations, finding improved accuracy with integrated multi-omics approaches.

This paper introduces encG-reg, an encrypted genotype regression method that identifies relatives across cohorts without sharing raw data, achieving accuracy comparable to traditional methods.

This paper introduces ALFDA, a machine learning method that improves identification of fine-scale genetic structure and preserves geogenetic distances better than existing methods.

This paper constructs a single-cell atlas of Alzheimer's disease brain tissue and identifies drug repositioning candidates by analyzing cellular heterogeneity and gene expression patterns.

deCS improves cell type annotation in scRNA-seq data by using a comprehensive human cell type reference atlas, enhancing accuracy and reducing computation time.

The paper identifies CXCR6 as a host genetic factor associated with severe COVID-19 through transcriptomic analysis and shows its protective effect in lung tissue.

TSEA identifies tissue-specific genes and enriches query data by analyzing multi-trait genome-wide association and cancer expression data.

This paper introduces Gene2Vec, a gene embedding method using co-expression data from GEO databases, showing improved pathway recovery and gene interaction prediction.

scRNASeqDB is a database that compiles human single-cell RNA-seq datasets for gene expression analysis and provides tools for querying and visualizing expression profiles.