Resources
SRT-Server for spatial transcriptomics data analysis
The current server is accessible here, with source code available on github.
Citation: Sheng Yang, and Xiang Zhou (2023). SRT-Server: Powering the analysis of spatial transcriptomic data. Genome Medicine.
PGS-Server for constructing polygenic scores in genome-wide association studies
The current server is accessible here, with source code available on github.
Citation: Sheng Yang, and Xiang Zhou (2022). PGS-server: Accuracy, robustness and transferability of polygenic score methods for biobank scale studies. Briefings in Bioinformatics. 23: bbac039.
eQTL mapping results on 1,032 African Americans and 801 European Americans in GENOA
Downlaod: cis-eQTL mapping summary statistics for African American and European American
Description of the above file format is available here.
All analysis code and scripts used in the paper are available on github.
Citation: Lulu Shang*, Jennifer A. Smith*, Wei Zhao, Minjung Kho, Stephen T. Turner, Thomas H. Mosley, Sharon L.R. Kardia#, Xiang Zhou# (2020). Genetic architecture of gene expression in European and African Americans: An eQTL mapping study in GENOA. American Journal of Human Genetics. 106: 496-512.
Contact Lulu Shang with any questions and comments.
meQTL mapping results on 961 African Americans in GENOA
Download: cis-meQTL mapping summary statistics for African Americans.
Description of the above file format is available here
All analysis code and scripts used in the paper are available on github.
Citation: Lulu Shang, Wei Zhao, Yi Zhe Wang, Zheng Li, Jerome Choi, Minjung Kho, Thomas H. Mosley, Sharon L.R. Kardia, Jennifer A. Smith#, Xiang Zhou# (2022). Genetic determinants of DNA methylation in African Americans: An meQTL mapping study in GENOA.
Contact Lulu Shang with any questions and comments.
Comparison of dimensionality reduction methods for single cell RNAseq analysis
In this study, we compared 11 different Dimensionality reduction (DR) methods on 28 publicly available scRNAseq data sets that cover a range of sequencing techniques and sample sizes. The performance of different DR methods are evaluated in terms of their accuracy and robustness in both cell clustering and lineage reconstruction downstream analyses.
All data, analysis code and scripts used in the paper are available on github.
Citation: Shiquan Sun, Jiaqiang Zhu, Ying Ma and Xiang Zhou (2019). Accuracy, robustness and scalability of dimensionality reduction methods for single-cell RNA-seq analysis. Genome Biology. 20: 269.
Contact Shiquan Sun with any questions and comments.