Featured Publications
2024
SVerma et al. (2024) . A multi-cohort genome-wide association study in African ancestry individuals reveals risk loci for primary open-angle glaucoma. https://doi.org/10.1016/j.cell.2023.12.006
DePaolo et al. (2024).Titin-Truncating variants Predispose to Dilated Cardiomyopathy in Diverse Populations. https://doi.org/10.1101/2024.01.17.24301405
Jee et al. (2024). Multi-ancestry polygenic risk scores for venous thromboembolism. https://doi.org/10.1101/2024.01.09.24300914
2023
Singhal et al. (2023). Evidence of epistasis in regions of long-range linkage disequilibrium across five complex diseases in the UK Biobank and eMERGE datasets. https://doi.org/10.1016/j.ajhg.2023.03.007
SVerma et al. (2023). Genome-Wide Association Study of Breast Density among Women of African Ancestry. https://doi.org/10.3390/cancers15102776
Penrod et al. (2023). Leveraging electronic health record data for endometriosis research. https://doi.org/10.3389/fdgth.2023.1150687
Xiao et al. (2023) Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions. https://doi.org/10.1161/JAHA.121.026561
2022
SVerma et al. (2022) Evaluating the frequency and the impact of pharmacogenetic alleles in an ancestrally diverse Biobank population. https://doi.org/10.1186/s12967-022-03745-5
Turong, Woemer & Cherlin et al. (2022). Quality control procedures for genome‐wide association studies. https://doi-org.proxy.library.upenn.edu/10.1002/cpz1.603
Hui and Xiao et al(2022). Quantifying factors that affect polygenic risk score performance across diverse ancestries and age groups for body mass index. https://doi.org/10.1142/9789811270611_0040
Pre-2021
SVerma et al. (2020). Research on COVID-19 through patient-reported data: a survey for observational studies in the COVID-19 pandemic. https://doi.org/10.1017/cts.2020.509
SVerma et al. (2018). Another Round of “Clue” to Uncover the Mystery of Complex Traits. https://doi.org/10.3390/genes9020061
SVerma et al. (2018). Rare variants in drug target genes contributing to complex diseases, phenome-wide.https://doi.org/10.1038/s41598-018-22834-4
SVerma et al. (2017).Identifying Genetic Associations With Variability In Metabolic Health And Blood Count Laboratory Values: Diving Into The Quantitative Traits By Leveraging Longitudinal Data From An EHR. https://doi.org/10.1142/9789813207813_0049
SVerma et al. (2016). Epistatic gene-based interaction analyses for glaucoma in eMERGE and NEIGHBOR consortium. https://doi.org/10.1371/journal.pgen.1006186
SVerma et al. (2014). Imputation and quality control steps for combining multiple genome-wide datasets. https://doi.org/10.3389/fgene.2014.00370