Shenzhen Bay Laboratory

Computational and Disease Genomics Lab


xQTLbiolinks (Briefings in Bioinformatics, 2023): A user-friendly R package, as the first end-to-end bioinformatics tool for efficient mining and analyzing public and user-customized xQTLs data for the discovery of disease susceptibility genes.

DaPars2 (Nature Genetics, 2021): A tool that directly infers the dynamic alternative polyadenylation (APA) usage by comparing standard RNA-seq from multiple samples.

scDaPars (Genome Research, 2021): A bioinformatics algorithm to accurately quantify Alternative Polyadenylation (APA) events at both single-cell and single-gene resolution using standard scRNA-seq data.

MAT3UTR (Nature Genetics, 2018): A mathematical model to quantify the trans effect of 3ʹ-UTR shortening to their affected ceRNA partner.


immune-3′aQTL (Nature Communications, 2023): This immune-3′aQTL a database provides 3' untranslated region (3'UTR) alternative polyadenylation (APA) quantitative trait loci (3'aQTLs) across in 18 human immune baseline cell types and 8 stimulation conditions.

scQTLbase (Nucleic Acids Research, 2023): The scQTLbase is an integrated human single-cell eQTL portal, which features 304 datasets across 57 cell types and 95 cell states and contains ~16 million SNPs significantly associated with gene expression in a certain cell type or status

ipaQTL-atlas (Nucleic Acids Research, 2022): The ipaQTL-atlas is a database for intronic polyadenylation based on 15,170 RNA-seq samples across 49 human Genotype-Tissue Expression (GTEx) project (version 8) tissues from 838 individuals.

3′aQTL-atlas (Nature Genetics, 2021): The 3′aQTL-atlas is a comprehensive list of 3′aQTLs, containing approximately 1.49 million SNPs associated with the APA of target genes, based on 15,201 RNA-seq samples across 49 human normal tissues isolated from 838 individuals

TC3A (Nucleic Acids Research, 2018): The Cancer 3′UTR Atlas (TC3A) is a repository to host a comprehensive compilation of APA events for more than ∼10,537 tumors across 32 cancer types (Note: The data can be accessed using doi:0.7303/syn24982198 or directly access synapse)