Selected Publications

Year 2023

• Li, X., Quick, C., Zhou, H., Gaynor, S., Liu, Y., Chen, H., Selvaraj, M., Sun, R., Dey, R., Arnett D., Bielak, L., Bis, J., Blangero, J., Boerwinkle, E., Bowden, D., Brody, J., Cade, B., Correa, A., Cupples, L.A., Curran, J., De Vries, P., Duggirala, R., Freedman, B., Goring, H., Guo, X., Haessler, J., Kalyani, R., Kooperberg, C., Kral, B., Lange, L., Manichaikul, A., Martin, L., McGarvey, S., Mitchell, B., Montasser, M., Morrison, A., Naseri, T., O'Connell, J., Palmer, N., Peyser, P., Psaty, B., Raffield, L., Redline, S., Reiner, A., Reupena, M., Rice, K., Rich, S., Sitlani, C., Smith, J., Taylor, K., Vasan, R., Wilson, J., Willer, C., Yanek, L., Zhao, W., NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group, Rotter, J., Natarajan, P., Peloso, G., Li, Z., Lin, X. (2023) Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies.Nature Genetics 55(1), 154-164
• Zhou, H., Arapoglou, T., Li, X., Li, Z., Zheng, X., Moore, J., Asok, A., Kumar, S., Blue, E.E., Buyske, S., Cox, N., Felsenfeld, A., Gerstein, M., Kenny, E., Li, B., Matise, T., Philippakis, A., Rehm, H.L., Sofia, H.J., Snyder, G., NHGRI Genome Sequencing Program Variant Functional Annotation Working Group, Weng, Z., Neale, B., Sunyaev, S.R., Lin, X. (2023). FAVOR: functional annotation of variants online resource and annotator for variation across the human genome.Nucleic Acids Research 51(D1), D1300-D1311

Year 2022

• Li, Z., Li, X., Zhou, H., Gaynor, S.M., Selvaraj, M., Arapoglou, T., Quick, C., Liu, Y., Chen, H., Sun, R., Dey, R., Arnett D., Auer, P., Bielak, L., Bis, J., Blackwell, T., Blangero, J., Boerwinkle, E., Bowden, D., Brody, J., Cade, B., Conomos, M., Correa, A., Cupples, L.A., Curran, J., De Vries, P., Duggirala, R., Franceschini, N., Freedman, B., Goring, H., Guo, X., Kalyani, R., Kooperberg, C., Kral, B., Lange, L., Lin, B., Manichaikul, A., Manning, A., Martin, L., Mathias, R., Mitchell, B., Montasser, M., Morrison, A., Naseri, T., O'Connell, J., Palmer, N., Peyser, P., Psaty, B., Raffield, L., Redline, S., Reiner, A., Reupena, M., Rice, K., Rich, S., Smith, J., Taylor, K., Taub, M., Vasan, R., Week, D., Wilson, J., Yanek, L., Zhao, W., NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group, Rotter, J., Willer, C., Natarajan, P., Peloso, G., Lin, X. (2022). A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies. Nature Methods 19(12), 1599-1611
• Li, X., Yung, G., Zhou, H., Sun, R., Li, Z., Hou, K., Zhang, M.J., Liu, Y., Arapoglou, T., Wang, C., Ionita-Laza, I., Lin, X. (2022). A multi-dimensional integrative scoring framework for predicting functional variants in the human genome. The American Journal of Human Genetics 109(3), 446-456
• Li, Z., Liu, Y., Lin X. (2022). Simultaneous detection of signal regions using quadratic scan statistics with applications in whole genome association studies. Journal of American Statistical Association 117(538), 823-834
• Liu, Y., Li, Z., Lin X. (2022). A minimax optimal ridge-type set test for global hypothesis with applications in whole genome sequencing association studies. Journal of American Statistical Association 117(538), 897-908
• Liu, Z., Shen, J., Barfield, R., Schwartz, J., Baccarelli, A., Lin, X. (2022). Large-Scale Hypothesis Testing for Causal Mediation Effects with Applications in Genome-wide Epigenetic Studies. Journal of American Statistical Association 117(537), 67-81
• Dey, R., Zhou, W., Kiiskinen, T., Havulinna, A., Elliott, A., Karjalainen, J., Kurki, M., Qin, A., FinnGen, Lee, S., Palotie, A., Neale, B., Daly, M., Lin, X. (2022). Efficient and accurate frailty model approach for genome-wide survival association analysis in large-scale biobanks. Nature Communications 13(1), 5437
• Gaynor, S.M., Westerman, K., Ackovic, L., Li, X., Li, Z., Manning, A., Philippakis, A., Lin, X. (2022). STAAR Workflow: A cloud-based workflow for scalable and reproducible rare variant analysis. Bioinformatics 38(11), 3116-3117
• Sun, R., Shi, A., Lin, X. (2022). Differences in set-based tests for sparse alternatives when testing sets of outcomes compared to sets of explanatory factors in genetic association studies. Biostatistics
• Lin, X. (2022). Lessons Learned from the COVID-19 Pandemic: A Statistician's Reflection. Statistical Science 37(2), 278-283
• Shi, A., Gaynor, S.M., Dey, R., Zhang, H., Quick, C., Lin X. (2022). COVID-19 Spread Mapper: a multi-resolution, unified framework and open-source tool. Bioinformatics 38(9), 2661-2663
• McCaw, Z.R., Gaynor, S.M., Sun, R., Lin X. (2022). Leveraging a surrogate outcome to improve inference on a partially missing target outcome. Biometrics
• Li, D., Ren, H., Varelmann, D.J., Sarin, P., Xu, P., Wu, D., Li, Q., Lin, X. (2022). Risk assessment for acute kidney injury and death among new COVID-19 positive adult patients without chronic kidney disease: retrospective cohort study among three US hospitals. BMJ open 12(2), e053635
• Byun, J.. Han, Y., Li, Y., ..., Lin, X., McKay, J., Hung, R. J., Amos, C. I, INTEGRAL-ILCCO Consortium (2022). Trans-ancestry genome-wide meta-analysis of 61,047cases and 947,237 controls identifies novel genomic cross-ancestry loci contributing to lung cancer susceptibility. Nature Genetics 54(8), 1167-1177
• Hong, D., Dey, R., Lin, X.*, Cleary, B.*, Dobriban, E.* (2022). Group testing via hypergraph factorization applied to COVID-19. Nature Communication 13, 1837 (* Co-corresponding authors)
• Selvaraj, M.S., Li, X., Li, Z., Pampana, A., Zhang, D.Y., Park, J., Aslibekyan, S., Bis, J.C., Brody, J.A., Cade, B.E. and Chuang, L.M.,..., Lin, X., Peloso, G., M., Natarajan, P. (2022) . Whole genome sequence analysis of blood lipid levels in> 66,000 individuals. Nature Communication 13, 5995

Year 2021

• Quick, C., Dey, R., & Lin, X. (2021). Regression Models for Understanding COVID-19 Epidemic Dynamics With Incomplete Data. Journal of the American Statistical Association 116(536), 1561-1577
• Li, D., Gaynor, S.M., Quick, C., Chen, J., Stephenson, B., Coull, B., Lin, X. (2021). Identifying US County-level characteristics associated with high COVID-19 burden. BMC public health 21(1), 1-10
• Naseri, A., Shi, J., Lin, X., Zhang, S., Zhi, D. (2021). RAFFI: Accurate and fast familial relationship inference using RaPID in Large Scale Biobank Studies. Plos Genetics 17(1): e1009315
• Ke, Z., Ma, Y., and Lin, X. (2021). Estimating the rank of a spiked covariance matrix by spectral quantile matching. Journal of the American Statistical Association
• Wang, X., Ricciuti, B.,Nguyen, T.,Li,X., Rabin, M. S., Awad, M. M.,Lin, X., Johnson, B., Christiani, D. C. (2021). Association between smoking history and tumor mutation burden in advanced non-small cell lung cancer. Cancer Research 81(9): 2566¨C2573
• Wang, X., Lin, X., Johnson, B., Christiani, D. C. (2021) .Smoking history as a potential predictor of immune checkpoint inhibitor (ICI) efficacy in metastatic non-small cell lung cancer (NSCLC). Journal of National Cancer Institute 113(12), 1761-1769
• Dayan, I., Roth. H., Zhong, Z., Harouni, A., ..., Lin, X., Wen, Y., Gilbert, F. J., Flores, M. G., Li, Q. (2021). Federated Learning used for predicting outcomes in SARS-COV-2 patients. Nature Medicine 27,1735-1743
• Wu, P., Ding, L., Li, X., Liu, S., Cheng, F., He, Q., Xiao, M., Wu, P., Hou, H., Jiang, M. and Long, P., Lin, X., Jin, X., Wang, F., Sun, C., and Wang, C. (2021) . Identifying US County-level characteristics associated with high COVID-19 burden. Communications biology 4(1), 1-10.

Year 2020

• Liu, Z., Barnett, I, and Lin, X. (2020) Differences in principal component methods between multiple phenotype regression and multiple SNP regression in genetic association studies. Annals of Applied Statistics 14(1), 433-451
• Raffield, L. M., Lyengar, A. K., Wang, B., Gaynor, S.M., Lin, X., Li, B., Li, Y., Dupuis, J., Reiner, A., Moklke, K.R., Auer, P. TOPMed Inflammation Working Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium. (2020) Allelic heterogeneity at the CRP locus identified by whole-genome sequencing in multi-ancestry cohorts. American Journal of Human Genetics 106(1), 112-120
• Pan, A., Liu, L., Wang, C., Guo, H., Hao, X., Wang Q., Huang, J., He, N., Yu, Ho, Lin, X.*, Wei, S.*, Wu, T.* (2020) Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China. Journal of the American Medical Association 323(19):1915-1923 (* Co-corresponding authors)
• Gao, X., Coull, B., Lin, X., Vokonas, P., Hou, L., DeMeo, D.L., Litonjua, A.A., Schwartz, J.D. and Baccarelli, A.A. (2020) Association of Neutrophil to Lymphocyte Ratio With Pulmonary Function in a 30-Year Longitudinal Study of US Veterans. JAMA Network Open 3(7), e2010350--e2010350
• Li, X., Li, Z., Zhou, H., Gaynor, S.M., Liu, Y., Chen, H., Sun, R., Dey, R., Arnett, D.K., Aslibekyan, S., Ballantyne, C.M., Bielak, L.F., Blangero, J., Boerwinkle, E., Bowden, D.W., Broome, J.G., Conomos, M.P., Correa, A., Cupples, L.A., Curran, J.E., Freedman, B.I., Guo, X., Hindy, G., Irvin, M.R., Kardia, SLR., Kathiresan, S., Khan, A.T., Kooperberg, C.L., Laurie, C.C., Liu, X.S., Mahaney, M.C., Manichaikul, A.W., Martin, L.W., Mathias, R.A., McGarvey, S.T., Mitchell, B.D., Montasser, M.E., Moore, J.E., Morrison, A.C., O'Connell, J.R., Palmer, N.D., Pampana, A., Peralta, J.M., Peyser, P.A., Psaty, B.M., Redline, S., Rice, K.M., Rich, S.S., Smith, J.A., Tiwari, H.K., Tsai, M.Y., Vasan, R.S., Wang, F., Weeks, D.E., Weng, Z., Wilson, J.G., Yanek, L.R., NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group, Neale, B.M., Sunyaev, S.R., Abecasis, G.R., Rotter, J.I., Willer, C.J., Peloso, G.M., Natarajan, P., and Lin, X. (2020) Dynamic incorporation of multiple in-silico functional annotations empowers rare variant association analysis of large whole genome sequencing studies at scale. Nature Genetics 52(9), 969-983
• Segal, E., Zhang, F., Lin, X., King, G., Shalem, O, Shilo, S, Allen, W., Grad, Y., Greene, C., Alquaddoomi, F., Anders, S., Balicer, R., Bauman, T., Bonilla, X, Booman, G., Chan, A., Cohen, O., Coletti, S., Davidson, N., Dor, Y., Drew D., Elemento, O., Evans, G., Ewels, P., Gale, J., Gavrieli, A., Geiger, G., Hajirasouliha, I., Jerala, R., Kahles, A., Kallioniemi, O, Keshet, A., Kocarev, L., Landua, G., Meir, T., Muller, A., Nguyen, A., Oresic, M., Ovchinnikova, S., Peterson, D. , Prodanova, J., Rajagopal, J., Rtsch, G., Rossman, H., Rung, J., Sboner, A., Sigaras, A., Spector, T., Steinherz, R., Stevens, I., Vilo, J., Wilmes, P. (2020) Building an International Consortium for Tracking Coronavirus Health Status Nature Medicine 26(8), 1161-1165
• Sun, R. and Lin, X. (2020). Genetic Variant Set-Based Tests Using the Generalized Berk-Jones Statistic With Application to a Genome-Wide Association Study of Breast Cancer Journal of the American Statistical Association 115 (531), 1079-1091
• McCaw, Z., Lane, J. M., Saxena, R., Redline, S., and Lin, X. (2020) . Normal Transformation Improves Genetic Association Testing with Quantitative Traits Biometrics 76(4), 1262-1272
• Allen, W. E. Altae-Tran, H., Briggs, J., Jin, X., McGee, G., Shi, A., Raghavan, R., Kamariza, M., Nova, N., ..., Travassos, M., Coull, B. A., Openshaw, J., Greene, C. S., Shalem, O., King. G., Probasco, R., Cheng, D., Silbermann, B., Zhang, F., and Lin, X. (2020). Population-scale Longitudinal Mapping of COVID-19 Symptoms, Behavior, and Testing Identifies Contributors to Continued Disease Spread in the United States Nature Human Behavior 4,972¨C982
• Hao, X., Cheng, S., Wu, D., Wu, T.*, Lin, X.* and Wang, C.* (2020) . Reconstruction of the full transmission dynamics of COVID-19 in Wuhan Nature 584(7821), 420-424. (* Co-corresponding authors)
• He, X., and Lin, X. (2020). Challenges and Opportunities in Statistics and Data Science: Ten Research Areas (with Discussions). Harvard Data Science Review 2(3)
• Lin, X. (2020). Learning Lessons on Reproducibility and Replicability in Large Scale Genome-Wide Association Studies. Harvard Data Science Review 2(4)
• Nguyen, L.H., Drew, D.A., Graham, M.S., Joshi, A.D., Guo, C.G., Ma, W., Mehta, R.S., Warner, E.T., Sikavi, D.R., Lo, C.H. and Kwon, S., ... Lin, X.,... Zhang, F (2020). Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. The Lancet Public Health 5(9), e475-e483
• Taliun, D., Harris, D.N., Kessler, M.D., Carlson, J., Szpiech, Z.A., Torres, R., Taliun, S.A.G., Corvelo, A., Gogarten, S.M., Kang, H.M. and Pitsillides, A.N., , Lin, X., , ..., Abecasis, G. (2020). Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature 590(7845), 290-299
• Sun, R., Xu. M., Li, X., Gaynor, S., Zhou, H., Bosse, Y. ...Mak, R., Barbie, D., Brennan, P., Hung, R., Amos, C. I. Christiani, D. C., Lin, X. (2020). Identification of Inflammation and Immune-Related Risk Variants Associated with Squamous Cell Lung Cancer Genetic Epidemiology 45(1), 99-114

Year 2019

• Fagny, M., Platig, J., Kuijjer, M.L., Lin, X., Quackenbush, J. (2019) Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function. British Journal of Cancer 122, 569-577
• Cade, B.E., Chen, H., Stilp, A.M., Louie, T., Ancoli-Israel, S., Arens, R., Barfield, R., Below, J.E., Cai, J., Conomos, M.P., Evans, D.S.,..., Zhu, X., Saxena, R., Lin, X., Redline, S. (2019) Associations of variants In the hexokinase 1 and interleukin 18 receptor regions with oxyhemoglobin saturation during sleep. PLoS genetics 15(4):e1007739
• Liang, J., Cade, B.E., He, K.Y., Wang, H., Lee, J., Sofer, T., Williams, S., Li, R., Chen, H., Gottlieb, D.J. and Evans, D.S., ..., Lin,X., ..., Redline, S., Zhu, X. (2019) Sequencing Analysis at 8p23 Identifies Multiple Rare Variants in DLC1 Associated with Sleep-Related Oxyhemoglobin Saturation Level. The American Journal of Human Genetics 105(5), 1057-1068
• Chen, S. and Lin, X. (2019) Analysis in case-control sequencing association studies with different sequencing depths. Biostatistics 21(3), 577-593
• Liu, Z. and Lin, X. (2019) A Geometric Perspective on the Power of Principal Component Association Tests in Multiple Phenotype Studies. Journal of the American Statistical Association 114(527), 975-990
• Chen, H., Huffman, J., Brody, J. A., Wang, C., Lee, S., Li, Z., Gogarten, S., Sofer, T., ..., Redline, S., Smith, N. L., Boerwinkle, E., Borecki, I. B., Cupples, L. A., Laurie, C., Morrison, A. C., Rice, K., M., Lin, X. (2019). Efficient variant set mixed model association tests for continuous and binary traits in large-scale whole genome sequencing studies. American Journal of Human Genetics 104(2), 260-274
• Gaynor, S., Sun, R., Lin, X., and Quackenbush, J. (2019) Genetic Variant Set-Based Tests Using the Generalized Berk-Jones Statistic With Application to a Genome-Wide Association Study of Breast Cancer Bioinformatics 35(22), 4568-4576
• Sun, R., Hui, S., Bader, G., Lin, X., and Kraft, P. (2019). Powerful Gene Set Analysis in GWAS with the Generalized Berk-Jones Statistic. Plos Genetics 15(3), p.e1007530.
• Liu, Y., Chen, S., Li, Z., Morrison, A. C., Boerwinkle, E., and Lin, X. (2019) ACAT: Fast and Powerful P-value Combination Method for Rare-variant Analysis in Sequencing Studies. American Journal of Human Genetics 104(3), 410-421
• Li, Z., Li, X., Liu, Y., Shen, J., Chen, H., Zhou, H., Morrison, A. C., Boerwinkle, E. and Lin, X. (2019) Dynamic Scan Procedure for Detecting Rare-Variant Association Regions in Whole-Genome Sequencing Studies American Journal of Human Genetics 104(5), 802-814
• Xu, M., Yao, Y., Chen, H., Zhang, S., Cao, S., Zhang, Z., Luo, B., Liu, Z., Li, Z., Xiang, T., H, G., Feng, Q., Chen, L., Guo, X., Jia, W., Chen, M., Zhang, X., Xie, S., Peng, R., Peng, R., Chang, E, Pedergnana, V., Feng, L., Bei, J., Xu, R., Zeng, M., Ye, W., Adami, H. O., Lin, X., Zhai, W., Zeng, Y. X., Liu, J. (2019). Genome sequencing analysis identifies Epstein-Barr virus subtypes associated with high risk of nasopharyngeal carcinoma. Nature Genetics 51(7), 1131-1136
• Barfield, R., Wang, H., Liu, Y., Brody, J., Swenson, B., Bartz, T. M., Sotoodehnia, N., Chen, Y. I., Cades, B., Chen, H., Patel, S. P., Sunyaev, S. R., Zhu, X., Gharib, S. A., Johnson, W.C., Rotter, J. I., Saxena, R., Purcell, S., Lin, X., Redline, S., Sofer, T. (2019). Epigenome-wide association analysis of daytime sleepiness in the Multi-Ethnic Study of Atherosclerosis reveals African-American specific associations. Sleep 42(8), p.zsz101.
• Peng, C. van Meel, E., Cardenas, A., Rifas-Shiman S., Sonawane, A., Glass, K., Gold, D. R., Platts-Mills, T. A., Lin, X., Oken, E., Hivert, M., Baccarelli, A. A., de Jong, N., Felix, J F., Jaddoe, V., Duijts, L, Litonjua, A. A., DeMeo, D. L, (2019). Epigenome-wide association study reveals methylation pathways associated with childhood allergic sensitization. Epigenetics 14(5), 445-466
• Wang, H., Cade, B., Sofer, T., Sands, S. A., Chen, H., ..., Sunyaev, S. R., Cai, J., Lin, X., Purcell, S. M., Laurie, C. C., Saxena, R., Redline, S., Zhu, X. (2019). Admixture mapping identifies novel loci for obstructive sleep apnea in Hispanic/Latino Americans. Human Molecular Genetics 28(4), 675-687

Year 2018

• Liu, Z. and Lin, X. (2018) Multiple Phenotype Association Tests Using Summary Statistics in Genome-Wide Association Studies. Biometrics 74(1), 165-175
• Sun, R., Carroll, R. J., Christiani, D. and Lin, X. (2018) Testing for gene-environment interaction under exposure misspecification. Biometrics 74(2), 653-663
• Gaynor, S., Schwartz, J., and Lin, X. (2018) Mediation analysis for common binary outcomes. Statistics in Medicine 38(4), 512-529
• Huang, J.V., Cardenas, A., Colicino, E., Schooling, C.M., Rifas-Shiman, S.L., Agha, G., Zheng, Y., Hou, L., Just, A.C., Litonjua, A.A. and DeMeo, D.L., Lin, X., Olkin, E., Hivert, M. F., Baccarelli, A. (2018) DNA methylation in blood as a mediator of the association of mid-childhood body mass index with cardio-metabolic risk score in early adolescence. Epigenetics 13(10-11), 1072-1087
• Carmona, J.J., Barfield, R.T., Panni, T., Nwanaji-Enwerem, J.C., Just, A.C., Hutchinson, J.N., Colicino, E., Karrasch, S., Wahl, S., Kunze, S. and Jafari, N., Lin, X., Schwartz, J., Schulz, H., Barccarelli, A. (2018) Metastable DNA methylation sites associated with longitudinal lung function decline and aging in humans: an epigenome-wide study in the NAS and KORA cohorts.  Epigenetics 13(10-11), 1039-1055
• Brunst, K.J., Tignor, N., Just, A., Liu, Z., Lin, X., Hacker, M.R., Bosquet Enlow, M., Wright, R.O., Wang, P., Baccarelli, A.A. and Wright, R.J. (2018) Cumulative lifetime maternal stress and epigenome-wide placental DNA methylation in the PRISM cohort. Epigenetics 13(6), 665-681
• Peng, C., Cardenas, A., Rifas-Shiman, S.L., Hivert, M.F., Gold, D.R., Platts-Mills, T.A., Lin, X., Oken, E., Baccarelli, A.A., Litonjua, A.A. and DeMeo, D.L. (2018) Epigenome-wide association study of total serum immunoglobulin E in children: a life course approach. Clinical epigenetics 10(1), 55
• Chen, S. and Lin, X. (2018) Analysis in case-control sequencing association studies with different sequencing depths. Biostatistics

Year 2017

• Barnett, I., Murkerjee, R. and Lin, X. (2017) The Generalized Higher Criticism for Testing SNP-set Effects in Genetic Association Studies. Journal of the American Statistical Association 112, 64-76
• Sofer, T., Schifano, E., D.,I., Lin, X. (2017) Weighted pseudo-likelihood for SNP set analysis with multiple secondary outcomes in case-control genetic association studies. Biometrics 73(4), 1210-1220
• Barfield, R., Shen, JC, Just, A., Schwartz, J., Baccarelli, A., VanderWeele, T., and Lin, X. (2017) Testing for the Indirect Effect Under the Null for Genome Wide Mediation Analyses. Genetic Epidemiology 41(8), 824-833
• Chen, J., Behnam, E, Huang, J., Moffatt, M., Schaid, D., Liang, L., Lin, X. (2017) Fast and robust adjustment of cell mixtures in epigenome-wide association studies with SmartSVA. BMC Genomics 18(1), 413

Year 2016

• Chen, J. Just, A. C., Schwartz, J., Hou, L, Jafari, L., Sun, Z, Baccarelli, A. and Lin, X. (2016) CpGFilter: Model-based CpG probe filtering with replicates for epigenome-wide association studies. Bioinformatics. 32.3, 469-471.
• Lin, X., Lee, S.,Wu, M.,Wang, C., Chen H., Li, Z. and Lin, X. (2016) Test for rare variants by environment interactions in sequencing association studies. Biometrics. 72.1, 156-164 Supplement. Software.
• Liang, J., Cade, BE, Wang, H., Chen, H., Larkin, EK, Saxena, R., Lin, X., Redline,S. and Zhu, X. (2016) Comparison of Heritability Estimation and Linkage Analysis for Multiple Traits Using Principal Component Analyses. Genetic Epidemiology. 40.3, 222-232.
• Chen, H., Wang, C., Conomos, MP, Stilp, AM, Li, Z., Sofer, T., Szpiro, AA, Chen, W., Brehm, JM, Celedon, JC, Redline, SS, Papanicolaou, GP, Thornton, TA, Laurie, CC, Rice, K. and Lin, X (2016) Control for population structure and relatedness for binary traits in genetic association studies using logistic mixed models. American Journal of Human Genetics. 98.4, 653-666.
• Yung, G. and Lin, X. (2016) Validity of Using Ad Hoc Methods to Analyze Secondary Traits in Case-Control Association Studies. Genetic Epidemiology. 40.8, 732-743.
• Wang, X., Zhang, Z., Morris, N., Cai, T., Lee, S., Wang, C., Timothy, W.Y., Walsh, C.A. and Lin, X. (2016) Rare variant association test in family-based sequencing studies. Briefings in Bioinformatics. p.bbw083.
• He, Q., Cai, T., Liu, Y., Zhao, N., Harmon, Q.E., Almli, L.M., Binder, E.B., Engel, S.M., Ressler, K.J., Conneely, K.N., Lin, X.and Wu, M. (2016) Prioritizing individual genetic variants after kernel machine testing using variable selection. Genetic Epidemiology. 40.8, 722-731.
• Xing, C., M McCarthy, J., Dupuis, J., Adrienne Cupples, L., B Meigs, J., Lin, X. and S Allen, A. (2016) Robust analysis of secondary phenotypes in case-control genetic association studies. Statistics in medicine. 35.23, 4226-4237.
• Liang J, Cade BE, Wang H, Chen H, Gleason KJ, Larkin EK, Saxena R, Lin X, Redline S and Zhu X. (2016) Comparison of Heritability Estimation and Linkage Analysis for Multiple Traits Using Principal Component Analyses. Genetic Epidemiology. 40.3, 222-32.

Year 2015

• Murkerjee, R., Pillai, N.S. and Lin, X. (2015) Hypothesis testing for sparse binary regression. Annals of Statistics. 43.1, 352-381.
• Wang, C., Zhan, X., Liang, L., Abecasis, G. R., and Lin, X. (2015) Improved Ancestry Estimation for both Genotyping and Sequencing Data using Projection Procrustes Analysis and Genotype Imputation. American Journal of Human Genetics 96, 926-937.
• Huang, Y., Liang, L, Moffatt, M., Cookson, W., and Lin, X. (2015). iGWAS: Integrative Genome-Wide Association Studies of Genetic and Genomic Data for Disease Susceptibility Using Mediation Analysis. Genetic Epidemiology. 39, 347-359.

Year 2014

• Huang. Y.T., VanderWeele, T.J., Lin, X. (2014) Joint analysis of SNP and gene expression data in genetic association studies of complex diseases. Annals of Applied Statistics. 8.1, 352-376.
• Valeri, L., Lin, X., VanderWeele, T. J. (2014) Mediation analysis when a continuous mediator is measured with error and the outcome follows a generalized linear model. Statistics in Medicine. 33.28, 4875-4890.
• Hu, T., Lin, X., Nan, B. (2014) Cross-Ratio Estimation for Bivariate Failure Times with Left Truncation. Life Time Data Analysis. 20.1, 23-37.
• Wong, J.Y., De Vivol, I., Lin, X., Grashow, R., Cavallari, J., Christiani, D.C. (2014) The association between global DNA methylation and telomere length in a longitudinal study of boilermakers. Genetic Epidemiology. 38.3, 254-264.
• Wong, J.Y.Y., De Vivol, I., Lin, X., Christiani, D.C. (2014) Cumulative PM2.5 exposure and telomere length in Workers exposed to welding fumes. Journal of toxicology and environmental health. <\i> 77.8, 441-455.
• Wong, J.Y.Y., De Vivol, I., Lin, X., Christiani, D.C. (2014) The relationship between inflammatory biomarkers and telomere length in an occupational prospective cohort study. PLoS One. 9.1, e87348.
• Barnett, I. and Lin, X. (2014) Analytic P-value calculation for the higher criticism test in finite d problems. Biometrika. 101.4, 964-970.
• Sofer, T., Dicker, L., Lin, X (2014) Variable selection for high-dimensional multivariate outcomes. Statistica Sinica. 24.4, 1633-1654.
• Wang, C., Zhan, X., Bragg-Gresham, J., Kang, H.M., Stambolian, D., Chew, E.Y., Branham, K., Heckenlively, J., The FUSION Study, Fulton, R., Wilson, R.K., Mardis, E.R., Lin, X., Swaroop, A., Zollner, S., Abecasis, G.R. (2014) Estimating individual ancestry using next generation sequencing. Nature Genetics. 46.4, 409-415.
• Lee, S., Abecasis, G., Boehnke, M., Lin, X. (2014) Rare-variant association analysis: Study designs and statistical tests. American Journal of Human Genetics. 95.1, 5-23.