Jin Liu

The paper identifies heritable telomere variant sequences that determine allele-specific telomere length and shows their role in telomere maintenance and inheritance.

This study identifies FSTL1's role in promoting vascular mimicry in HCC via interaction with PDCD4 and activation of the PI3K/AKT/mTOR pathway, suggesting it as a potential therapeutic target.

SpatialAnno improves spatial transcriptomics annotation by integrating non-marker genes and spatial information without a reference dataset.

FAST improves spatial dimension reduction for multi-section SRT data by modeling count data and spatial smoothness, showing better performance and speed on real datasets.

PRECAST integrates spatial transcriptomics data from multiple sources, improving cell and domain detection through probabilistic embedding, clustering, and alignment.

SpatialDEG identifies differentially expressed genes in spatially resolved transcriptomic data by integrating spatial information, showing controlled type-I error rates in simulations and applied to human and mouse datasets.

This study assembles and compares the mitochondrial genomes of three Macadamia species, revealing gene composition, evolutionary relationships, and selection pressures.

This paper introduces DR-SC, a method that jointly performs dimension reduction and spatial clustering for single-cell and spatial transcriptomics data, improving accuracy and biological relevance.

SC-MEB is a spatial clustering method for transcriptomics data that outperforms existing methods in clustering performance and scalability.

This paper introduces TisCoMM, a tissue-specific collaborative mixed model for TWAS that improves gene-trait association detection and identifies tissue-specific gene roles in complex traits.

This paper introduces PMR-Egger, a probabilistic Mendelian randomization method to test and control horizontal pleiotropy in transcriptome-wide association studies, showing improved type I error control and power.

This paper introduces MR-LDP, a Mendelian randomization method that accounts for linkage disequilibrium and horizontal pleiotropy, showing improved causal inference in GWAS summary statistics.

IGREX quantifies the impact of genetically regulated expression on phenotypes using GWAS data and gene expression reference panels, showing significant phenotypic variation explained by GREX effects.

CoMM-S2 uses GWAS summary statistics to infer mechanistic roles of genetic variants in gene expression, achieving performance comparable to methods using individual-level data.

The paper identifies three mutational subtypes in UTUC linked to AA exposure, aging, and DNA repair, with distinct clinical outcomes and therapeutic implications.

The paper improves radiation dose estimation by automating dicentric chromosome curation and metaphase cell selection, reducing false positives and increasing accuracy.