Chiang.Lab

Tsz Fung Chan is a Ph.D student in the group since 2019. He is pursuing his Ph.D. in Epidemiology in the Department of Preventive Medicine. Co-advised by both Dr. Chiang and Dr. Nicholas Mancuso in the Center for Genetic Epidemiology, he is currently developing methods to estimate heritability of complex traits explained by local ancestry and to evaluate stratification bias in admixture mapping studies. Before joining the group, Tsz Fung studied the genetics of Epstein-Barr virus under the guidance of Alan Chiang and Wanling Yang at the University of Hong Kong. He received his Bachelor of Biomedical Sciences (with a minor in Computer Sciences) and M.Phil in Bioinformatics from University of Hong Kong in 2017 and 2019, respectively.

Recent publications:

1. Langie J, Chan TF, Yang W, Kang AY, Morimoto L, Stram DO, Mancuso N, Ma X, Metayer C, Lupo PJ, Rabin KR, Scheurer ME, Wiemels JL, Yang JJ, de Smith AJ*, Chiang CWK*. “The impact of Indigenous American-like ancestry on risk of acute lymphoblastic leukemia in Hispanic/Latino children.” medRxiv 2025. preprint.
   
   
2. Lo YC, Tian H, Chan TF, Jeon S, Alatorre K, Dinh BL, Maskarinec G, Taparra K, Nakatsuka N, Yu M, Chen CY, Lin YF, Wilkens LR, Le Marchand L, Haiman CA, Chiang CWK. “Transferability of polygenic scores for anthropometric traits and Type II Diabetes to the Native Hawaiian population.” Accepted at Comms Bio. 2025.
   
   
3. de Smith AJ*, Wahlster L*, Jeon S*, Kachuri L, Black S, Cato LD, Nakatsuka N, Chan TF, Langie J, Mazumder S, Yang W, Gazal S, Eng C, Hu D, Buchard EG, Ziv E, Metayer C, Mancuso N, Yang JJ, Ma X, Wiemels JL, Yu F*, Chiang CWK*, Sankaran VG*. “A noncoding regulatory variant in IKZF1 increases acute lymphoblastic leukemia risk in Hispanic/Latino children.” Cell Genom. 2024 Apr 10;4(4):100526. link
   
   
4. Chan TF, Rui X, Conti DV, Fornage M, Graff M, Haessler J, Haiman C, Highland HM, Jung SY, Kenny E, Kooperberg C, Le Marchand L, North KE, Tao R, Wojcik G, Gignoux CR, PAGE Consortium, Chiang CWK*, Mancuso N*. “Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics.” Am J Hum Genet. 2023 Nov 2;110(11):1853-1862. link
   
   
5. Li S, Chiang CWK, Myint SS, Arroyo K, Chan TF, Morimoto L, Metayer C, de Smith AJ, Walsh KM, Wiemels JL. “Localized variation in ancestral admixture identifies pilocytic astrocytoma risk loci among Latino children.” PLoS Genet. 2022 Sep 7;18(9):e1010388. link
   
   
6. Jeon S, de Smith AJ, Li S, Chen M, Chan TF, Muskens IS, Morimoto LM, Dewan AT, Mancuso N, Metayer C, Ma X, Wiemels JL, Chiang CWK. “Genome-wide trans-ethnic meta-analysis identifies novel susceptibility loci for childhood acute lymphoblastic leukemia.” Leukemia. 2022 Mar;36(3):865-868. link
   
   
7. Sun H*, Lin M*, Russell EM, Minster RL, Chan TF, Dinh BL, Naseri T, Reupena MS, Lum-Jones A, OLaGA Study Group, Cheng I, Wilkens LR, Le Marchand L, Haiman CA, Chiang CWK. “The impact of global and local Polynesian genetic ancestry on complex traits in Native Hawaiians.” PLoS Genet. 2021 Feb 11. link
   
   

Bryan Dinh is a Ph.D. student in the group since 2020. He is an F31 predoctoral fellow pursuing his Ph.D. in the Computational Biology and Bioinformatics program in the Department of Biological Sciences. Bryan is interested in algorithms and their applications to biology, genetics, and diverse populations. Supported by a F31 predoctoral fellowship from NHGRI, Bryan's dissertation focuses on constructing and evaluating genomic resources for Native Hawaiian community, with the goal to empower cutting edge genomic studies in this understudied population. Before joining the group, Bryan received a Master of Science in Computer Science and a Bachelor of Science in Mathematics and Economics from UCSD.

Recent publications:

1. Lo YC, Tian H, Chan TF, Jeon S, Alatorre K, Dinh BL, Maskarinec G, Taparra K, Nakatsuka N, Yu M, Chen CY, Lin YF, Wilkens LR, Le Marchand L, Haiman CA, Chiang CWK. “Transferability of polygenic scores for anthropometric traits and Type II Diabetes to the Native Hawaiian population.” Accepted at Comms Bio. 2025.
   
   
2. Fan C, Cahoon JL, Dinh BL, Ortega-Del Vecchyo VD, Huber CD, Edge MD, Mancuso N, Chiang CWK. “A likelihood-based framework for demographic inference from genealogical trees.” In press at Nat Genet. 2025.
   
   
3. Dinh BL, Tang E, Taparra K, Nakatsuka N, Chen F, Chiang CWK. “Recombination map tailored to Native Hawaiians may improve robustness of genomic scans for positive selection.” Hum Genet. 2024 Jan;143(1):85-99. link
   
   
4. Link V, Schraiber JG, Fan C, Dinh BL, Mancuso N, Chiang CWK, Edge MD. “Tree-based QTL mapping with expected local genetic relatedness matrices.” Am J Hum Genet. 2023 Dec 7;110(12):2077-2091. link
   
   
5. Sun H*, Lin M*, Russell EM, Minster RL, Chan TF, Dinh BL, Naseri T, Reupena MS, Lum-Jones A, OLaGA Study Group, Cheng I, Wilkens LR, Le Marchand L, Haiman CA, Chiang CWK. “The impact of global and local Polynesian genetic ancestry on complex traits in Native Hawaiians.” PLoS Genet. 2021 Feb 11. link
   
   

Jalen Langie is a Ph.D. student in the group since 2021. She is a F31 predoctoral fellow pursuing a Ph.D. in Epidemiology (Genetic Track) in the Department of Population and Public Health Sciences. Overall, she aims to investigate genetic contributions to disease through the lens of evolutionary history. Her interests include admixture mapping, fine mapping, and SNP-to-gene annotations in multiethnic populations. Prior to joining the lab, she received her Bachelor of Science in Microbiology from California State University Los Angeles in 2019. During undergraduate, she worked as a research assistant for three years studying fungal pathogenesis and regulatory pathways and completed an internship studying viral kinetics and chemokine expression at Johns Hopkins University.

Recent publications:

1. Langie J, Chan TF, Yang W, Kang AY, Morimoto L, Stram DO, Mancuso N, Ma X, Metayer C, Lupo PJ, Rabin KR, Scheurer ME, Wiemels JL, Yang JJ, de Smith AJ*, Chiang CWK*. “The impact of Indigenous American-like ancestry on risk of acute lymphoblastic leukemia in Hispanic/Latino children.” medRxiv 2025. preprint.
   
   
2. Cahoon JL, Rui X*, Tang E*, Simons C, Langie J, Chen M, Lo YC, Chiang CWK. “Imputation Accuracy Across Global Human Populations.” Am J Hum Genet. 2024 May 2;111. link
   
   
3. de Smith AJ*, Wahlster L*, Jeon S*, Kachuri L, Black S, Cato LD, Nakatsuka N, Chan TF, Langie J, Mazumder S, Yang W, Gazal S, Eng C, Hu D, Buchard EG, Ziv E, Metayer C, Mancuso N, Yang JJ, Ma X, Wiemels JL, Yu F*, Chiang CWK*, Sankaran VG*. “A noncoding regulatory variant in IKZF1 increases acute lymphoblastic leukemia risk in Hispanic/Latino children.” Cell Genom. 2024 Apr 10;4(4):100526. link.
   
   

Dorcus Kholofelo Malomane is a postdoctoral research scholar in the group since 2022. She is interested in exploring patterns of genetic variation in diverse human populations and their relation to complex traits. Dorcus has a background in population and evolutionary genomics. She obtained her PhD in 2019 from the University of Goettingen, Germany. In her PhD work she studied how different geographic distributions, management and breeding practices have shaped genetic diversity in a wide variety of globally collected chicken populations. Furthermore, she investigated the genetic patterns of different genomic regions, pathways and genes in the chicken to explore their subjection to different evolutionary dynamics. Prior to joining the group, she was shortly a postdoctoral research associate at the University of Goettingen and her work was aimed at developing genetic markers for ash dieback disease. Her current project utilizes the genome-wide array data, whole exome and genome sequencing data to understand the impact of population structure and history on patterns of variation in a Saudi population.

Recent publications:

1. Malomane DK, Williams MP, Huber CD, Mangul S*, Abedalthagafi M*, Chiang CWK*. “Patterns of population structure and genetic variation within the Saudi Arabian population.” bioRxiv 2025. preprint
   
   

Xinran Wang started as a Program Analyst in 2023 and is now a Ph.D. student in the lab since 2024. She is passionate about leveraging genomic data to gain insights into disease-trait associations, the evolution and architecture of complex traits, and the history of diverse human populations. At present, Xinran's work primarily focuses on evaluating imputation reference panel for Japanese and Native Hawaiian populations, as well as conducting GWAS and meta-analyses on hyperemesis gravidarum. Before joining the lab, she earned her Master of Science in Applied Biostatistics and Epidemiology from the University of Southern California and her Bachelor of Arts in Public Health from UC Irvine. During her master's program, Xinran gained valuable experience in GWAS, meta-analysis, and TWAS while working under the supervision of Dr. Nicholas Mancuso at USC and Dr. Marlena Fejzo at USC and UCLA.

He Tian is a Ph.D. student in the group since 2023. She is pursuing her Ph.D. in Epidemiology in the Department of Population and Public Health Sciences. She is interested in Polygenic Risk Scores and cancers among ethnic minority populations. Before joining the lab, she received her Bachelor of Medicine in Preventive Medicine from Shandong University (Jinan, China) in 2020. During graduate school, she focused on studying the racial disparity in ovarian cancer and received her MPH in 2022.

Recent publications:

1. Lo YC, Tian H, Chan TF, Jeon S, Alatorre K, Dinh BL, Maskarinec G, Taparra K, Nakatsuka N, Yu M, Chen CY, Lin YF, Wilkens LR, Le Marchand L, Haiman CA, Chiang CWK. “Transferability of polygenic scores for anthropometric traits and Type II Diabetes to the Native Hawaiian population.” Accepted at Comms Bio. 2025.
   
   

Ji Tang obtained a Bioinformatics Ph.D. in July 2023 from the Southern Medical University of China. He was awarded as the Outstanding Graduate in his Ph.D., where he developed a deep learning method for identifying the genomic mutations favored by recent natural selection and investigated the association between adaptive evolution and disease susceptibility in human populations. In general, Ji is interested in investigating the influence of population history on the genetic architecture of traits/diseases in diverse human populations by developing computational methods (especially machine learning methods) and performing statistical analyses. Currently, he is focusing on developing a method to infer more accurate ARG (Ancestral Recombination Graph) when applied to empirical sequencing data with errors, and on demonstrating the enrichment of functionally important or consequential alleles in Polynesian-ancestry individuals, whose ancestors went through several bottlenecks and persisted in small population sizes for a long time.

Recent publications:

1. Tang J, Chiang CWK. “A genealogy-based approach for revealing ancestry-specific structures in admixed populations.” bioRxiv 2025. preprint
   
   

Indu Sharma is a postdoctoral research fellow since 2023. She is a highly accomplished researcher with a Ph.D. in Biotechnology from India, having previously worked as a Population Geneticist at New York University Abu Dhabi campus. Indu's research has predominantly centered on underrepresented and tribal populations, particularly those from Northwestern India and the Northwestern Himalayas. Her expertise in population genomics has allowed her to delve into the evolutionary impacts and gene-based associations of various complex disorders prevalent in South Asian endogamous groups. Her current research aims at unraveling the selection signatures within the Native Hawaiian population. Her work combines the precision of population genomics with a keen understanding of complex genetic traits.

Eunice Lee is a senior research associate who joined the lab in 2023. She was born in Seoul, South Korea, and moved to and grew up in Southern California when she was young. She was trained as an environmental and genetic epidemiologist focusing on asthma in minority children and cardiovascular diseases in the adult U.S. population. Her main research interests are population genetics, computational toxicology, and gene and environment interactions using various statistical methods and machine learning algorithms. Outside of work, Eunice started rock climbing, taking pottery lessons, and enjoys outdoor activities such as hiking and camping.

Kimberli Alatorre started as an intern in the lab and is now a programmer analyst since 2024. She is a recent graduate of the University of California, Santa Barbara, where she earned a Bachelor of Science in Biological Sciences. Aspiring to pursue a career in medicine, she aims to specialize in pediatrics, with a focus on serving underserved communities. Her academic interests include Polygenic Risk Scores (PRS) and the heritability of complex traits and diseases. A native of Los Angeles, Kimberli enjoys hiking, spending time at the beach, and running outdoors in her free time.

Recent publications:

1. Lo YC, Tian H, Chan TF, Jeon S, Alatorre K, Dinh BL, Maskarinec G, Taparra K, Nakatsuka N, Yu M, Chen CY, Lin YF, Wilkens LR, Le Marchand L, Haiman CA, Chiang CWK. “Transferability of polygenic scores for anthropometric traits and Type II Diabetes to the Native Hawaiian population.” Accepted at Comms Bio. 2025.
   
   

Eaaswarkhanth Muthukrishnan joined the lab in 2024 as a research associate. Originally from Pollachi, a charming town nestled near the Western Ghats of Tamil Nadu, south of India, Eaaswar brings a wealth of experience as a population geneticist with postdoc and staff scientist roles in diverse international labs. His research work includes uncovering complex evolutionary trajectories in shaping the human skin-barrier function, developing a robust analytical framework for analyzing genomic structural variants and identifying genetic bases of human phenotypic variation. Among his key research findings, Eaaswar has shed light on the evolutionary factors behind high rates of metabolic syndrome in Kuwait, characterized genetic variants related to lactase persistence in the Indian subcontinent, and tracked evolutionary trends in SARS-CoV-2 virus. His doctoral research established historical population movements by tracing sub-Saharan African genetic lineage within a non-tribal Indian population, a study that remains a key reference for understanding the origins and genetic diversity of South Asian Muslims. Currently, his research centers on the fine-scale population structure, genetic history and demographic patterns of Native Hawaiian and East Asian populations.

Lab Activities

We don't just work hard, we play hard too! Click here for some pictures of the lab events and activities over the years!

Image credit: modified from "Group" by Nawicon / CC

Lab Alumni

All of the wonderful trainees, visitors, and colleagues that have contributed to our work!

Hanxiao Sun, M.S. Biostatistics 2018-2019. Last known location: Postdoc at Memorial Sloan Kettering Cancer Center with Jian Carrot-Zhang
Meng Lin, postdoc 2018-2020. Last known location: staff scientist at University of Colorado with Chris Gignoux
Samuel Sommerer, B.S. Quantitative Biology 2019-2020. Last known location: B.S. student in Computer Science at USC
Sydney Rashid, B.S. Quantitative Biology 2019-2020. Last known location: B.S. student in Quantitative Biology at USC
Minhui Chen, postdoc 2018-2021. Last known location: staff scientist at University of Chicago with Andy Dahl
Camellia Xinyue Rui, M.S. Biostatistics 2020-2022. Last known location: Ph.D. student at USC
Ying Chu Lo, postdoc 2021-2023.
Christopher Simons, B.S./M.S. Quantitative Biology 2021-2023. Last known location: Bioinformatician at Design Therapeutics
Soyoung Jeon, Ph.D. Cancer Biology and Genomics 2018-2023. Last known location: Bioinformatic scientist at Active Motif
Caoqi Fan, Ph.D. Computational Biology and Bioinformatics 2019-2023. Last known location: Bioinformatic scientist at Vibrant Therapeutics
Echo Tang, B.S. Quantitative Biology 2021-2023. Last known location: M.S. student in Public Health Data Sciences at USC
Jordan Cahoon, B.S. Computer Science 2021-2024. Last known location: Ph.D. student in Biomedical Data Science at Stanford

Image credit: modified from "Graduation" by Wilson Joseph / CC

Join Our Group

We are always interested in talented and highly motivated individuals to join our team! We currently have space and funding for one or more postdoctoral fellows in genetic epidemiology and population genetics to join our group. Please check out this page for expectations and resources for lab members. See below for how to apply:

Postdoctoral Fellows: Highly motivated individuals are encouraged to contact Charleston Chiang for inquiries. In particular, there are openings for postdocs either interested in population genetics or in genetic epidemiology. Funding could be through a R35 grant, an anticipated R01, unrestricted funds, or through the USC-UH Multiethnic Cohort T32 Postdoctoral Training Program. Applicants ideally should have extensive exposure and experience in human medical and/or population genetics research and have analyzed large genetic datasets. Programming skills (e.g. python, perl, C, R, etc.) and proficiency in Unix-based computing environments are very desirable. Successful candidates may also develop projects broadly within the scope of the group's research interests.

Informal inquiries or applications (cover letter, CV, and contact information to at least two references) should be emailed to Charleston Chiang.

Graduate Students: The research group is recruiting prospective PhD students. Generally, doctoral students are enrolled through Program in Biological and Biomedical Sciences (PIBBS), Computational Biology and Bioinformatics (CBB) or one of the Public Health Sciences programs (such as Biostatistics or Epidemiology) at USC. Email Charleston Chiang for inquiries.

Image credit: "Unknown" by Bybzee / CC BY