Human population and statistical genetics

We investigate how human history shapes global genetic and phenotypic diversity, and the role these forces play in predisposing people to various complex disease risks and evolutionarily important traits. We are also particularly interested in conducting increasingly diverse studies to reduce health disparities induced by vast Eurocentric genetic study biases. We are based in the Analytic & Translational Genetics Unit in Massachusetts General Hospital as well as the Stanley Center for Psychiatric Research at the Broad Institute.

Research Areas


Our group focuses on diverse population studies in the following areas:

Empowering large-scale genomic studies across complex traits and diverse populations

The vast majority of participants in genetic studies are of European descent, limiting the generalizability of genetic technologies across globally diverse populations. While the fundamental biology discovered by genetic studies at specific sites in the genome are mostly shared across humanity, Eurocentric study biases mean we miss low-hanging fruit in other populations and limit disease risk prediction accuracy from polygenic scores in globally diverse populations. We currently predict heritable complex diseases risk several-fold more accurately in European ancestry populations than in genetically diverged populations. As genomic studies increase in scale, they explain more heritable variation and hold greater potential for clinical translation, but their implementation today would exacerbate health disparities. To ameliorate these issues while accelerating genomic discoveries, we are increasing the scale and diversity of genomic studies (e.g., Pan-UK Biobank Project, Global Biobank Meta-analysis Initiative, and other studies). (Learn more)

The heritable basis of psychiatric disorders in diverse populations

Psychiatric disorders such as schizophrenia and bipolar disorder are highly heritable and account for a large proportion of the global burden of disease. Genetics therefore provides major opportunities in psychiatry, both for understanding disease etiology and as biomarkers. However, genetic findings in psychiatric genetic studies have largely come from European ancestry cohorts. Humans originated in Africa, so African populations are the most genetically diverse globally yet are vastly underrepresented in medical genetics research. To this end, we are developing public genomics resources of diverse African genomes related to the Genome Aggregation Database (gnomAD). We are also conducting population and statistical genetic analyses in the Neuropsychiatric Genetics in African Populations (NeuroGAP) study, which is enrolling and sequencing the genomes of >35,000 participants in a case/control study spanning Ethiopia, Kenya, South Africa, and Uganda. As part of an umbrella project, we also help coordinate the data analysis team in the Population Underrepresented in Mental illness Association Studies (PUMAS) project, which is building a sample bank and will be sequencing the genomes of 120,000 people to medium coverage across cases and controls across African and Latin American populations. In a parallel research capacity building effort, we also actively contribute to the Global Initiative for Neuropsychiatric Genetics Education in Research (GINGER) Program. (Learn more)

Human evolution and fine-scale population history

We are interested in using genetic data to look back through time to learn about how demographic history, including migration, admixture, and population size changes, shaped human history. Understanding human evolutionary history has implications for study design, interpreting and accounting for population stratification, learning about the genetic architecture of complex traits, and gaining insights into forces of natural selection. We are especially interested in understanding the genetic basis of traits that have been evolutionarily important throughout human history, such as skin pigmentation and height, and how they changed throughout the human diaspora. To this end, we have focused in several geographic areas, including on very recent admixture in the Americas, recent history for the bottlenecked Finnish population, and with a particular emphasis on deeper and more complex history in sub-Saharan Africa. (Learn more)



team member
Alicia Martin Assistant Professor

As a population and statistical geneticist, my research examines the role of human history in shaping global genetic and phenotypic diversity. Given vast Eurocentric study biases, my group quantifies the transferability of knowledge gained from large-scale genetic studies across globally diverse populations. I am particularly interested in ensuring that the translation of genetic technologies via polygenic risk does not exacerbate health disparities induced by these study biases. Towards this end, we are developing statistical methods, community resources, and research capacity for multi-ancestry studies.

Postdoctoral Research Fellows

team member
Toni Boltz Postdoctoral Fellow

Toni is a postdoctoral research fellow in Dr. Alicia Martin's lab. She completed her PhD in Human Genetics at the University of California, Los Angeles where she focused on functional genomics of neuropsychiatric disorders using transcriptomics, chromatin accessibility, and metabolomics datasets. In October of 2023 she joined the ATGU where she is interested in using diverse genomics datasets to further investigate the genetic basis of neuropsychiatric disorders in underrepresented populations.

team member
Yixuan He Postdoctoral Fellow

Yixuan (pronounced yi-shwin) is a postdoctoral research fellow in Dr. Alicia Martin’s lab. She did her PhD in Bioinformatics and Integrative Genomics at Harvard Medical School as a NSF graduate research fellow. Her PhD thesis focused on new methods to integrate environmental and clinical data to predict disease risk. She is broadly interested in developing methods that combine clinical, genetic, and other non-genetic risk factors from large-scale datasets to predict disease risk across diverse populations. Outside of lab, she loves to bake and play with her Australian shepherd.

team member
Lerato Majara Postdoctoral Fellow

I have a background in Medical Microbiology having completed my undergraduate and MSc degrees in this field. I slightly shifted fields to pursue a PhD in Human Genetics at the University of Cape Town (UCT). My PhD thesis investigated the genetic risk factors associated with schizophrenia in the South African Xhosa population. I am an alumni member of the Global Initiative of Neuropsychiatric Genetics Education and Research (GINGER) programme at Harvard T.H. Chan School of Public Health, and currently pursuing a Postdoctoral fellowship on the Neuropsychiatric Genetics in African Populations (NeuroGAP) project. When I am not doing research, I tutor mathematics to high school learners for a non-profit organization called Fun Learning for Youth (FLY). I also enjoy running on road and trail, hiking and visiting food markets in my downtime.

team member
Yue Shi Postdoctoral Fellow

Yue Shi is a research fellow in Dr. Alicia Martin’s lab. She obtained with an MD degree from Sun Yat-sen University, specialized in Reproductive Medicine. Her MD research focused on the Application of Whole-exome Sequencing for Precision Medicine Research on Female Reproduction. She is widely interested in uncovering the genetic basis of diseases and exploring the clinical application of genetic risk factors. Outside of work, she enjoys a variety of sports activities, including Taekwondo, swimming, tennis, and badminton.

team member
Ying Wang Postdoctoral Fellow

Ying is a postdoctoral research fellow in Dr. Alicia Martin’s lab. She did her PhD in statistical/quantitative genetics at the University of Queensland. During her PhD, she worked on the application of genomic prediction methods in diverse ancestry populations and development of such methods to improve transferability of polygenic scores in trans-ancestry predictions. She has a broad interest in research areas related to multi-ancestry studies and population genetics.

PhD Students

team member
Yon Ho Jee Graduate Student

Yon Ho is a PhD student in the Program in Genetic Epidemiology and Statistical Genetics at Harvard T.H. Chan School of Public Health. Co-advised by Peter Kraft and Alicia Martin, her research focuses on leveraging samples with diverse ancestries to better understand the genetic architecture of complex traits and improve polygenic risk scores.

team member
Kristin Tsuo Graduate Student

Kristin is a PhD student in the Biological and Biomedical Sciences (BBS) program at Harvard Medical School, co-advised by Alicia Martin and Mark Daly. She is broadly interested in developing approaches to study disease risk prediction in diverse populations, and in particular, leveraging biobank data to model genetic and non-genetic contributors to human disease. She grew up in Princeton, New Jersey, and completed her undergraduate degree in Integrative Biology at Harvard. Outside of the lab, she enjoys attending dance workshops, playing cello, and hunting for a New Jersey-quality bagel in Boston (spoiler: there are none).

Computational Associates

team member
Zan Koenig Associate Computational Biologist

Zan is an Computational Associate at the Broad Institute. They are interested in creating community tools which contribute to overall global health equity. Under the mentorship of Alicia Martin and Elizabeth Atkinson, they are working on running analyses and developing tools for datasets with diverse ancestry populations such as NeuroGAP-Psychosis, HGDP, and the 1000 Genomes Project. Zan graduated from Rensselaer Polytechnic Institute in 2019 with a BS in Bioinformatics and Molecular Biology. In their free time they enjoy painting, hiking, knitting, and playing games of all kinds.

team member
Lindo Nkambule Associate Computational Biologist

Lindo is an Associate Computational Biologist in the Martin and Neale Labs at the Broad Institute. He is interested in the development of tools/software to analyse and visualise genomic data. Lindo completed his Honours degree in Bioinformatics in 2019 and his project was on assessing the sensitivity and accuracy of various variant callers in African populations. He also likes ice cream and sneaker shopping.

team member
Sophie Parsa Associate Computational Biologist

Sophie is a computational associate in the Karczewski and Martin labs. She is interested in creating deep learning models from genomic sequencing data. She completed a BS in Computer Science and a MS in Biomedical Informatics, both at Stanford. She is passionate about the intersection of computer science and medicine.

team member
Mary T. Yohannes Associate Computational Biologist

Mary is an Associate Computational Biologist at the Broad Institute. She is originally from Addis Ababa, Ethiopia. She completed her undergraduate study in Biology with a concentration in Mathematical Biology and Bioinformatics (Pre-Medical track) at Clark University in 2019 and graduated from Boston University in 2020 with an MS in Bioinformatics. She is currently working on running QC pipelines for the HGDP+1000 Genomes Project under the supervision of Alicia Martin. Additionally, she has been working with Tarjinder Singh, a postdoctoral fellow in the Analytic and Translational Genetics Unit, to develop a pipeline for calculating genome-wide sequencing coverage of Schizophrenia data. She plans to continue working on projects that allow her to apply her classroom knowledge/experiences while acquiring new ones. She is interested in the application of bioinformatics in medicine and hopes to eventually go back and work in her home country. Outside of work, Mary enjoys spending time with friends and her Bible study small groups, loves exploring new food places, and finds joy in making people laugh.

MS Students

team member
Yunfei (Daisy) Lyu MS Student

Daisy is a master student in the Computational Biology and Quantitative Genetics program at Harvard. She completed her BS in Genetics and Genomics at Duke Kunshan University. She is broadly interested in population genetics and evolution. Currently, she is working on a project exploring the correlation between genetic structure and ethnolinguistic diversity. In her spare time, she enjoys sports and outdoor activities such as swimming, hiking, and bird watching.

Lab Alumni

    Chengzhen (Cheng) Dai, former MS student, currently Sr. Staff Software Engineer at Quizlet

Friends of the lab

team member
Elizabeth G. Atkinson Assistant Professor

The Atkinson lab is a close collaborator of ours, working on improving genomics for underserved groups via improvements to statistical and population genetics. Their work is centered around neuropsychiatric traits with particular focus on admixed populations. Learn more about the Atkinson lab.



For most up to date list, see Google scholar page or My Bibliography

  • Atkinson, E. G., Dalvie, S., Pichkar, Y., Kalungi, A., Majara, L., Stevenson, A., … Martin, A.R., NeuroGAP-Psychosis Study Team. (2022). Genetic structure correlates with ethnolinguistic diversity in eastern and southern Africa. The American Journal of Human Genetics, 109(9), 1667–1679. doi:10.1016/j.ajhg.2022.07.013
  • Kullo, I. J., Lewis, C. M., Inouye, M., Martin, A.R., Ripatti, S., & Chatterjee, N. (2022). Polygenic scores in biomedical research. Nature Reviews. Genetics, 23(9), 524–532. doi:10.1038/s41576-022-00470-z
  • Wang, Y., Tsuo, K., Kanai, M., Neale, B. M., & Martin, A.R. (2022). Challenges and opportunities for developing more generalizable polygenic risk scores. Annual Review of Biomedical Data Science, 5(1), 293–320. doi:10.1146/annurev-biodatasci-111721-074830
  • Martin, A.R., Stroud, R. E., 2nd, Abebe, T., Akena, D., Alemayehu, M., Atwoli, L., … Chibnik, L. B. (2022). Increasing diversity in genomics requires investment in equitable partnerships and capacity building. Nature Genetics, 54(6), 740–745. doi:10.1038/s41588-022-01095-y
  • Ruan, Y., Lin, Y.-F., Feng, Y.-C. A., Chen, C.-Y., Lam, M., Guo, Z., … Ge, T. (2022). Improving polygenic prediction in ancestrally diverse populations. Nature Genetics, 54(5), 573–580. doi:10.1038/s41588-022-01054-7
  • Mars, N., Kerminen, S., Feng, Y.-C. A., Kanai, M., Läll, K., Thomas, L. F., … Ripatti, S. (2022). Genome-wide risk prediction of common diseases across ancestries in one million people. Cell Genomics, 2(4), None.
  • Weissbrod, O., Kanai, M., Shi, H., Gazal, S., Peyrot, W. J., Khera, A. V., … Price, A. L. (2022). Leveraging fine-mapping and multipopulation training data to improve cross-population polygenic risk scores. Nature Genetics, 54(4), 450–458. doi:10.1038/s41588-022-01036-9
  • Fatumo, S., Chikowore, T., Choudhury, A., Ayub, M., Martin, A.R., & Kuchenbaecker, K. (2022). A roadmap to increase diversity in genomic studies. Nature Medicine, 28(2), 243–250. doi:10.1038/s41591-021-01672-4
  • Camarena, B., Atkinson, E. G., Baker, M., Becerra-Palars, C., Chibnik, L. B., Escamilla-Orozco, R., … Koenen, K. C. (2021). Neuropsychiatric genetics of psychosis in the Mexican population: A genome-wide association study protocol for schizophrenia, schizoaffective, and bipolar disorder patients and controls. Complex Psychiatry, 7(3–4), 60–70. doi:10.1159/000518926
  • Polygenic Risk Score Task Force of the International Common Disease Alliance. (2021). Responsible use of polygenic risk scores in the clinic: potential benefits, risks and gaps. Nature Medicine, 27(11), 1876–1884. doi:10.1038/s41591-021-01549-6
  • Turley, P., Meyer, M. N., Wang, N., Cesarini, D., Hammonds, E., Martin, A.R., … Visscher, P. M. (2021). Problems with using polygenic scores to select embryos. The New England Journal of Medicine, 385(1), 78–86. doi:10.1056/NEJMsr2105065
  • Martin, A.R., Atkinson, E. G., Chapman, S. B., Stevenson, A., Stroud, R. E., Abebe, T., … NeuroGAP-Psychosis Study Team. (2021). Low-coverage sequencing cost-effectively detects known and novel variation in underrepresented populations. The American Journal of Human Genetics, 108(4), 656–668. doi:10.1016/j.ajhg.2021.03.012
  • Atkinson, E. G., Maihofer, A. X., Kanai, M., Martin, A.R., Karczewski, K. J., Santoro, M. L., … Neale, B. M. (2021). Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power. Nature Genetics, 53(2), 195–204. doi:10.1038/s41588-020-00766-y
  • Gay, N. R., Gloudemans, M., Antonio, M. L., Abell, N. S., Balliu, B., Park, Y., … Montgomery, S. B. (2020). Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx. Genome Biology, 21(1), 233. doi:10.1186/s13059-020-02113-0
  • Ávila-Arcos, M. C., McManus, K. F., Sandoval, K., Rodríguez-Rodríguez, J. E., Villa-Islas, V., Martin, A.R., … Moreno-Estrada, A. (2020). Population history and gene divergence in Native Mexicans inferred from 76 human exomes. Molecular Biology and Evolution, 37(4), 994–1006. doi:10.1093/molbev/msz282
  • Dai, C. L., Vazifeh, M. M., Yeang, C.-H., Tachet, R., Wells, R. S., Vilar, M. G., … Martin, A.R. (2020). Population histories of the United States revealed through fine-scale migration and haplotype analysis. The American Journal of Human Genetics, 106(3), 371–388. doi:10.1016/j.ajhg.2020.02.002
  • Lam, M., Chen, C.-Y., Li, Z., Martin, A.R., Bryois, J., Ma, X., … Huang, H. (2019). Comparative genetic architectures of schizophrenia in East Asian and European populations. Nature Genetics, 51(12), 1670–1678. doi:10.1038/s41588-019-0512-x
  • Peterson, R. E., Kuchenbaecker, K., Walters, R. K., Chen, C.-Y., Popejoy, A. B., Periyasamy, S., … Duncan, L. E. (2019). Genome-wide association studies in ancestrally diverse populations: Opportunities, methods, pitfalls, and recommendations. Cell, 179(3), 589–603. doi:10.1016/j.cell.2019.08.051
  • Nievergelt, C. M., Maihofer, A. X., Klengel, T., Atkinson, E. G., Chen, C.-Y., Choi, K. W., … Koenen, K. C. (2019). International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci. Nature Communications, 10(1), 4558. doi:10.1038/s41467-019-12576-w
  • J Grove, S Ripke, TD Als, M Mattheisen, R Walters, H Won, et al. (2019). Common risk variants identified in autism spectrum disorder. Nature Genetics
  • Palk, A.C., Dalvie, S., de Vries, J., Martin, A.R., Stein, D.J. (2019) Potential use of clinical polygenic risk scores in psychiatry–ethical implications and communicating high polygenic risk. Philosophy, Ethics, and the Humanities in Medicine.
  • Stevenson, A., Akena, D., Stroud, R.E., Atwoli, L., Campbell, M.M., Chibnik, L.B., et al. (2019) Neuropsychiatric Genetics of African Populations-Psychosis (NeuroGAP-Psychosis): a case-control study protocol and GWAS in Ethiopia, Kenya, South Africa and Uganda. BMJ Open 9, e025469–9
  • Quillen, E. E. et al. (2018). Shades of complexity: New perspectives on the evolution and genetic architecture of human skin. Am. J. Phys. Anthropol. 69, 167–23
  • Martin, A.R., Daly, M.J., Robinson, E.B., Hyman, S.E., Neale, B.M. (2018) Predicting polygenic risk of psychiatric disorders. Biological Psychiatry.
  • Lin, M., Siford*, R.L, Martin*, A.R., Nakagome, S., Moller, M., Hoal, E.G., Bustamante, C.D., Gignoux, C.R., Henn, B.M. (2018). Rapid evolution of a skin-lightening allele in southern African KhoeSan. Proceedings of the National Academy of Sciences 115, 13324–13329
  • Martin, A. R., Teferra, S., Möller, M., Hoal, E. G. & Daly, M. J. The critical needs and challenges for genetic architecture studies in Africa. Current Opinion in Genetics & Development 53, 113–120 (2018).
  • Demontis D, Walters RK, Martin J, Mattheisen M, Als TD, Agerbo E, et al. (2018). Discovery of the first genome-wide significant risk loci for ADHD. Nature Genetics 51, 63–75
  • GL Wojcik, C Fuchsberger, D Taliun, R Welch, AR Martin, S Shringarpure, et al. (2018). Imputation aware tag SNP selection to improve power for multi-ethnic association studies. G3: Genes, Genomes, Genetics 8 (10), 3255-3267
  • Ganna, A., Satterstrom, F.K., Zekavat, S.M., Das, I., Kurki, M.I., Churchhouse, C., Alfoldi, J., Martin, A.R., Havulinna, A.S., Byrnes, A., et al. (2018). Quantifying the Impact of Rare and Ultra-rare Coding Variation across the Phenotypic Spectrum. Am. J. Hum. Genet. 102, 1204–1211.
  • Martin, A.R., Lin, M., Granka, J.M., Myrick, J.W., Liu, X., Sockell, A., Atkinson, E.G., Werely, C.J., Möller, M., Sandhu, M.S., et al. (2017). An Unexpectedly Complex Architecture for Skin Pigmentation in Africans. Cell 171, 1340–1353.e14. [Online] [In the media] [Related popular press]
  • Martin, A.R., Karczewski, K.J., Kerminen, S., Kurki, M., Sarin, A.-P., Artomov, M., Eriksson, J.G., Esko, T., Genovese, G., Havulinna, A.S., et al. (2018). Haplotype sharing provides insights into fine-scale population history and disease in Finland. AJHG. 102, 760–775. [Online]
  • Kerminen, S., Havulinna, A.S., Hellenthal, G., Martin, A.R., Sarin, A.-P., Perola, M., Palotie, A., Salomaa, V., Daly, M.J., Ripatti, S., et al. (2017). Fine-Scale Genetic Structure in Finland. G3 7, 3459–3468. [Online] [In the News]
  • Martin, A. R., Gignoux, C. R., Walters, R., Wojcik, G. L., Gravel, S., Daly, M. J., Bustamante, C. D., Kenny, E. E. (2017). Human demographic history impacts genetic risk prediction across diverse populations. American Journal of Human Genetics. 100, 635-649. [Featured article] [Cotterman Award]
  • Duncan, L. E., Ratanatharathorn, A., Aiello, A. E., Almli, L. M., Amstadter, A. B., Ashley-Koch, A. E., et al. (2017). Largest GWAS of PTSD (N=20,070) Yields Genetic Overlap with Schizophrenia and Sex Differences in Heritability. Molecular Psychiatry. [Online]
  • Uren, C., Kim, M., Martin, A. R., Granka, J. M., Werely, C. J., Kidd, J. M., Bobo, D., Gignoux, C. R., Behr, A., Ramachandran, S., van Helden, P., Möller, M., Hoal, E. G., Henn, B. M. (2016). Fine-scale population structure in southern Africa reflects ecological boundaries. Genetics. 204, 303-314. [Online]
  • Henn, B. M.*, Botigué, L. R.*, Peishl, S.*, Dupanloup, I., Lipatov, M., Maples, B. K., Martin, A. R., Musharoff, S., Yee, MC, Cann, H. M., Snyder, M., Excoffier, L., Kidd, J. M., Bustamante, C. D. (2016). Distance from Sub-Saharan Africa Predicts Mutational Load in Diverse Human Genomes. PNAS. 113, E440-E449. [Online]
  • The 1000 Genomes Project Consortium. (2015). A global reference for human genetic variation. Nature. 526. 68-74. [Online] [In the news]
  • Grubert, F.*, Zaugg, J. B.*, Kasowski, M.*, Ursu, O.*, Spacek, D. V., Martin, A. R., et al. (2015). Genetic Control of Chromatin States and Gene Expression in Humans Involves Local and Distal Chromosomal Interactions. Cell. 162, 1051-1065. [Online] [In the news]
  • Martin, A. R.*, Costa, H. A.*, Lappalainen, T., Henn, B. M., Kidd, J. M., Yee, M. C., Grubert, F., Cann, H.M., Snyder, M., Montgomery, S. B., Bustamante, C.D. (2014). Transcriptome Sequencing from Diverse Human Populations Reveals Differentiated Regulatory Architecture. PLoS Genetics. 10, e1004549. [Online] [In the news]
  • Martin, A.R., Tse, G., Bustamante, C. D., Kenny, E. E. (2014). Imputation-based Assessment of Next Generation Rare Exome Variant Arrays. Pacific Symposium for Biocomputing. 241-252. [Online]
  • Kidd, J. M.*, Sharpton, T. J.*, Bobo, D., Norman, P. J., Martin, A. R., Carpenter, M. L., et al. (2014). Exome Capture from Saliva Produces High Quality Genomic and Metagenomic Data. BMC Genomics. 15, 262. [Online] [In the news]
  • Karczewski, K. J., Fernald, G. H., Martin, A. R., Snyder, M., Tatonetti, N. P., Dudley, J. T. (2014). STORMSeq: An Open-Source, User-Friendly Pipeline for Processing Personal Genomics Data in the Cloud. PLoS One. 9, e84860. [Online]
Lab News

Lab news

  • 🎳 6/15/23: We enjoyed a summertime celebration of science with some candlepin bowling!

  • 🖌️️ 12/2/22: We celebrated Lerato's visit and exciting science with some pottery painting!

  • The group is multi-talented, with many artistic hobbies!

  • 🧬️️ 10/27/22: We enjoyed conference season with some great lab representation at ASHG!

  • The Martin, Karczewski, and Atkinson Labs enjoyed a tasty joint dinner in LA! 🌮

  • 🌎 12/7/21: The lab has contributed substantially to work in the Global Biobank Meta-analysis Initiative!

  • 🎉 11/5/21: With so much to celebrate, we enjoyed dinner and games together!

  • After a lengthy visa saga, Lindo joined us in Boston! We also celebrated ASHG presentations from Kristin and Zan (with significant support from Ying and Mary, respectively), Lerato finalizing PhD corrections at UCT, Allan Kalungi visiting the lab from Makerere University, and Kristin and Ying finishing drafts of their first manuscripts from the lab! The lab is now a year old (😮) and several people celebrated work anniversaries!

  • 🧺 6/11/21: We had our first in-person lab event - a poke picnic with bocce!

  • Kristin winds up for some competitive action.

    The lab hangs out while our live mascot seeks squirrels.

  • 🎉 5/14/21: Kristin passed her preliminary qualifying exam. Congratulations Kristin!

  • 👋 5/10/21: Ying Wang joined the lab as a postdoctoral research fellow. She is especially interested in the generalizability of polygenic scores across diverse populations. Welcome Ying!

  • 🎉 1/14/21: Lerato Majara wrote her first first author paper, now on bioRxiv. Congratulations Lerato!


team member

Pan-UK Biobank Project

Learn more here.
Github repo here.

team member
HGDP + 1000 Genomes Project

Latest release here.
(Note: we are aware of some QC issues that removed especially diverse populations from this version and will be updating shortly.)
Github repo here.

team member
GWASpy pipeline

Our open-source scalable pipeline for conducting QC, PCA, phasing, and imputation in the cloud is under development!
Github repo here.



Alicia Martin

Analytic and Translational Genetics Unit
Massachusetts General Hospital
Richard B. Simches Research Center
185 Cambridge Street, CPZN-6818
Boston, MA 02114