Qi Yan

Qi Yan

Statistical Geneticist, Biostatistician and Bioinformatician qy2253@cumc.columbia.edu

Selected publications

  1. Yan, Q., Blue, N.R., Truong, B., Zhang, Y., Guerrero, R.F., et al. (2023). Genetic associations with dynamic placental proteins identify causal biomarkers for hypertension in pregnancy. MedRxiv (under revision in Am J Obstet Gynecol).
  2. Yan, Q., Guerrero, R.F., Khan, R.R., Surujnarine, A.A., Wapner, R.J., et al. (2023). Searching and visualizing genetic associations of pregnancy traits by using GnuMoM2b. Genetics.
  3. Yan, Q., Forno, E., Celedon, J.C., Chen. W., Weeks, D.E. (2021). Allele-specific method for testing the association between molecular quantitative traits and phenotype-genotype interaction. Bioinformatics.
  4. Yan, Q., Forno, E., Celedon, J.C., Chen. W. (2021). A region-based method for causal mediation analysis of DNA methylation data. Epigenetics.
  5. Yan, Q., Forno, E., Cardenas, A., Qi, C., Han, Y.Y., et al. (2021). Exposure to violence, chronic stress, nasal DNA methylation, and atopic asthma in children. Pediatric Pulmonology.
  6. Yan, Q., Weeks, D.E., Xin, H., Swaroop, A., Chew, E.Y., et al. (2020). Deep-learning-based Prediction of Late Age-Related Macular Degeneration Progression. Nature Machine Intelligence.
  7. Yan, Q., Jiang, Y., Huang, H., Swaroop, A., Chew, E.Y., et al. (2020). GWAS-based Machine Learning for Prediction of Age-Related Macular Degeneration Risk. TVST.
  8. Yan, Q., Forno, E., Yang, G., Herrera-Luis, E., Pino-Yanes, M., et al. (2020). A genome-wide association study of asthma hospitalizations in adults. J Allergy Clin Immunol.
  9. Yan, Q., Forno, E., Herrera-Luis, E., Pino-Yanes, M., Qi, C., et al. (2020). A genome-wide association study of severe asthma exacerbations in Latino children and adolescents. Eur Respir J.
  10. Jiang, Y.^, Chiu, C.^, Yan, Q., Chen, W., Gorin, M.B., Conley, Y.P., Lakhal-Chaieb, M.L., Cook, R.J., Amos, C.I., Wilson, A.F., et al. (2019). Gene-based Association Testing of Dichotomous Traits with Generalized Linear Mixed Models Using Extended Pedigrees. Journal of the American Statistical Association.
  11. Yan, Q., Liu, N., Forno, E., Canino, G., Celedon, J.C., and Chen, W. (2019). An integrative association method for omics data based on a modified Fisher’s method with application to childhood asthma. PLoS Genet.
  12. Kamboh, M.I.^, Fan, K.H.^, Yan, Q.^, Beer, J.C., Snitz, B.E., Wang, X., Chang, C.H., Demirci, F.Y., Feingold, E., and Ganguli, M. (2019). Population-based genome-wide association study of cognitive decline in older adults free of dementia: identification of a novel locus for the attention domain. Neurobiol Aging. ^co-first-author.
  13. Forno, E.^, Wang, T.^, Qi, C.^, Yan, Q., Xu, C.J., Boutaoui, N., Han, Y.Y., Weeks, D.E., Jiang, Y., Rosser, F., et al. (2019). DNA methylation in nasal epithelium, atopy, and atopic asthma in children: a genome-wide study. Lancet Respir Med.
  14. Yan, Q., Nho, K., Del-Aguila, J.L., Wang, X., Risacher, S.L., Fan, K.H., Snitz, B.E., Aizenstein, H.J., Mathis, C.A., Lopez, O.L., et al. (2018). Genome-wide association study of brain amyloid deposition as measured by Pittsburgh Compound-B (PiB)-PET imaging. Mol Psychiatry.
  15. Yan, Q., Ding, Y., Liu, Y., Sun, T., Fritsche, L.G., Clemons, T., Ratnapriya, R., Klein, M.L., Cook, R.J., Liu, Y., et al. (2018). Genome-wide analysis of disease progression in age-related macular degeneration. Hum Mol Genet 27, 929-940.
  16. Yan, Q., Fang, Z., and Chen, W. (2018). KMgene: a unified R package for gene-based association analysis for complex traits. Bioinformatics 34, 2144-2146.
  17. Wen, X.^, Liu, Y.^, Yan, Q.^, Liang, M., Tang, M., Liu, R., Pan, J., Liu, Q., Chen, T., Guo, S., et al. (2018). Association of IGFN1 variant with polypoidal choroidal vasculopathy. J Gene Med 20, e3007. ^co-first-author.
  18. Yan, Q., Brehm, J., Pino-Yanes, M., Forno, E., Lin, J., Oh, S.S., Acosta-Perez, E., Laurie, C.C., Cloutier, M.M., Raby, B.A., et al. (2017). A meta-analysis of genome-wide association studies of asthma in Puerto Ricans. Eur Respir J.
  19. Yan, Q., Chen, R., Sutcliffe, J.S., Cook, E.H., Weeks, D.E., Li, B., and Chen, W. (2016). The impact of genotype calling errors on family-based studies. Sci Rep.
  20. Yan, Q., Weeks, D.E., Tiwari, H.K., Yi, N., Zhang, K., Gao, G., Lin, W.Y., Lou, X.Y., Chen, W., and Liu, N. (2015). Rare-Variant Kernel Machine Test for Longitudinal Data from Population and Family Samples. Hum Hered.
  21. Yan, Q., Weeks, D.E., Celedon, J.C., Tiwari, H.K., Li, B., Wang, X., Lin, W.Y., Lou, X.Y., Gao, G., Chen, W., et al. (2015). Associating Multivariate Quantitative Phenotypes with Genetic Variants in Family Samples with a Novel Kernel Machine Regression Method. Genetics.
  22. Fan, R.^, Wang, Y.^, Yan, Q.^, Ding, Y., Weeks, D.E., Lu, Z., Ren, H., Cook, R.J., Xiong, M., Swaroop, A., et al. (2016). Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions. Genet Epidemiol. ^co-first-author.
  23. Yan, Q., Tiwari, H.K., Yi, N., Gao, G., Zhang, K., Lin, W.Y., Lou, X.Y., Cui, X., and Liu, N. (2015). A Sequence Kernel Association Test for Dichotomous Traits in Family Samples under a Generalized Linear Mixed Model. Hum Hered 79, 60-68.
  24. Yan, Q., Tiwari, H.K., Yi, N., Lin, W.Y., Gao, G., Lou, X.Y., Cui, X., and Liu, N. (2014). Kernel-machine testing coupled with a rank-truncation method for genetic pathway analysis. Genet Epidemiol.
  25. Yan, Q., McDonald, J.M., Zhou, T., and Song, Y. (2013). Structural insight for the roles of fas death domain binding to FADD and oligomerization degree of the Fas-FADD complex in the death-inducing signaling complex formation: a computational study. Proteins.
  26. Yan, Q., Murphy-Ullrich, J.E., and Song, Y. (2011). Molecular and structural insight into the role of key residues of thrombospondin-1 and calreticulin in thrombospondin-1-calreticulin binding. Biochemistry.
  27. Yan, Q., Murphy-Ullrich, J.E., and Song, Y. (2010). Structural insight into the role of thrombospondin-1 binding to calreticulin in calreticulin-induced focal adhesion disassembly. Biochemistry.