Jianxin Shi

This paper identifies 116 risk loci for melanoma through GWAS, links susceptibility to immunity and Wnt signaling, and develops a PRS improving risk prediction.

The paper identifies biologically distinct subtypes of MDD based on energy-related symptoms and finds genetic and metabolic differences between them.

The paper presents an isoform-level lung cell atlas using single-cell long-read RNA-sequencing, revealing genetic effects on isoform regulation that improve cell-type classification and identify novel variants associated with lung cancer risk.

The paper constructs a single-cell eQTL dataset from Asian never-smokers, identifying alveolar cell-specific genes linked to lung cancer susceptibility.

The paper identifies functional variants and VNTRs at the 5p15.33 locus using fine-mapping, MPRA, and CRISPRi screens, revealing their role in cancer susceptibility through antagonistic pleiotropy.

This study identifies RAPGEF1 as a gene modulating melanoma and nevi risk through RAS activation, using fine-mapping, expression data, and functional assays.

This paper develops a deep learning model to predict molecular alterations in never-smoker lung adenocarcinomas from histological images, achieving high accuracy for most features.

The paper identifies rs3769823 as a functional variant near CASP8 influencing its expression in a cell-type specific manner and associated with multiple cancers.

This study identifies three distinct evolutionary trajectories in lung adenocarcinomas using whole-genome sequencing, revealing that some never-smoking tumors follow smoking-like paths driven by KRAS mutations.

GFBioNet identifies genomic factors modulating trait-trait relationships in multi-omics data, revealing host genetics, microbial taxa, and mutations affecting biological networks.

The paper presents a multi-tissue sheep atlas identifying regulatory variants and their effects on molecular phenotypes, revealing allelic heterogeneity and evolutionary patterns.

The paper develops and validates multi-ancestry polygenic risk scores for LUAD in East Asian never-smokers, showing improved risk prediction compared to East Asian-only models.

The paper identifies three subtypes of NS-LUAD using RNA-seq data and develops a 60-gene signature that predicts survival across subgroups.

This study analyzes 1024 lung adenocarcinomas to identify evolutionary patterns and mutational mechanisms, revealing distinct trajectories linked to smoking, ancestry, and retrotransposition.

The paper identifies cell-type specific lung cancer susceptibility genes by integrating single-cell multi-omics data with GWAS loci.

The paper identifies two lung cancer subtypes defined by APOBEC mutagenesis levels and shows their association with different genetic mutations, aging, and immune responses.

The paper investigates the shared genetic etiology between chronic diseases and heart failure risk, finding that longer leukocyte telomere length mediates a small portion of the asthma PRS effect on HF risk.

This paper introduces SATS, a framework for mutational signature analysis in targeted sequencing data, and presents a pan-cancer catalogue of mutational signatures from 111,711 tumors.

The paper estimates the fraction of phenotypic variance explained by high-dimensional genomic predictors with measurement error, using microbiome data from the American Gut Project.

The paper introduces microbiomeGWAS, a tool to identify host genetic variants associated with microbiome composition using beta diversity metrics and corrects for statistical biases in pairwise distance data.

SUITOR selects the optimal number of mutational signatures using cross-validation, improving accuracy over existing methods in cancer genomics.

This paper develops a transcriptome-based polygenic risk score (T-PRS) linking depression-related cortical gene expression changes to brain morphology and symptom severity in MDD.

The paper identifies cell-type-specific meQTLs in melanocytes and melanomas, enhancing GWAS annotation and revealing regulatory mechanisms involving IRF4.

This study examines intratumor heterogeneity and clonal evolution in papillary renal cell carcinomas using whole-genome sequencing and DNA methylation data, revealing distinct patterns of genomic and epigenomic evolution across subtypes.

This study quantifies genetic and epigenetic intratumor heterogeneity in lung adenocarcinoma and links it to poor prognosis.

The paper identifies three immune subtypes in luminal breast cancer through immune gene expression profiling and links them to distinct genomic and clinical features.

This paper shows that GWAS using minimal phenotyping for depression identifies non-specific genetic factors shared with other psychiatric conditions, not specific to major depressive disorder.

The paper identifies allele-specific open chromatin (ASoC) variants in human iPSC-derived neurons and shows their strong enrichment in brain disorder risk variants.

This study investigates whether genetic variation in the Major Histocompatibility Complex (MHC) is associated with depression risk, finding no significant associations at a conservative threshold.

SummaryAUC approximates the AUC of polygenic risk scores using only summary statistics from validation datasets, enabling efficient evaluation of PRS models.