Contact

  • Academic
    allyk@stanford.edu
    University - Student Department: School of Medicine Position: Graduate, Medicine

All Publications

  • A harmonized public resource of deeply sequenced diverse human genomes. Genome research Koenig, Z., Yohannes, M. T., Nkambule, L. L., Zhao, X., Goodrich, J. K., Kim, H. A., Wilson, M. W., Tiao, G., Hao, S. P., Sahakian, N., Chao, K. R., Walker, M. A., Lyu, Y., Rehm, H., Neale, B. M., Talkowski, M. E., Daly, M. J., Brand, H., Karczewski, K. J., Atkinson, E. G., Martin, A. R. 2024

    Abstract

    Underrepresented populations are often excluded from genomic studies due in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high quality set of 4,094 whole genomes from 80 populations in the HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also demonstrate substantial added value from this dataset compared to the prior versions of the component resources, typically combined via liftOver and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared to previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

    View details for DOI 10.1101/gr.278378.123

    View details for PubMedID 38749656

  • Multiracial Reading the Mind in the Eyes Test (MRMET): An inclusive version of an influential measure. Behavior research methods Kim, H. A., Kaduthodil, J., Strong, R. W., Germine, L. T., Cohan, S., Wilmer, J. B. 2024

    Abstract

    Can an inclusive test of face cognition meet or exceed the psychometric properties of a prominent less inclusive test? Here, we norm and validate an updated version of the influential Reading the Mind in the Eyes Test (RMET), a clinically significant neuropsychiatric paradigm that has long been used to assess theory of mind and social cognition. Unlike the RMET, our Multiracial Reading the Mind in the Eyes Test (MRMET) incorporates racially inclusive stimuli, nongendered answer choices, ground-truth referenced answers, and more accessible vocabulary. We show, via a series of large datasets, that the MRMET meets or exceeds RMET across major psychometric indices. Moreover, the reliable signal captured by the two tests is statistically indistinguishable, evidence for full interchangeability. We thus present the MRMET as a high-quality, inclusive, normed and validated alternative to the RMET, and as a case in point that inclusivity in psychometric tests of face cognition is an achievable aim. The MRMET test and our normative and validation data sets are openly available under a CC-BY-SA 4.0 license at osf.io/ahq6n.

    View details for DOI 10.3758/s13428-023-02323-x

    View details for PubMedID 38630159

    View details for PubMedCentralID 6640856

  • A harmonized public resource of deeply sequenced diverse human genomes. bioRxiv : the preprint server for biology Koenig, Z., Yohannes, M. T., Nkambule, L. L., Goodrich, J. K., Kim, H. A., Zhao, X., Wilson, M. W., Tiao, G., Hao, S. P., Sahakian, N., Chao, K. R., Rehm, H. L., Neale, B. M., Talkowski, M. E., Daly, M. J., Brand, H., Karczewski, K. J., Atkinson, E. G., Martin, A. R. 2023

    Abstract

    Underrepresented populations are often excluded from genomic studies due in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high quality set of 4,096 whole genomes from HGDP and 1kGP with data from gnomAD and identified over 159 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also demonstrate substantial added value from this dataset compared to the prior versions of the component resources, typically combined via liftover and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared to previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

    View details for DOI 10.1101/2023.01.23.525248

    View details for PubMedID 36747613

    View details for PubMedCentralID PMC9900804

  • Phenotype and genetic analysis of data collected within the first year of NeuroDev. Neuron Kipkemoi, P., Kim, H. A., Christ, B., O'Heir, E., Allen, J., Austin-Tse, C., Baxter, S., Brand, H., Bryant, S., Buser, N., de Menil, V., Eastman, E., Murugasen, S., Galvin, A., Kombe, M., Ngombo, A., Mkubwa, B., Mwangi, P., Kipkoech, C., Lovgren, A., MacArthur, D. G., Melly, B., Mwangasha, K., Martin, A., Nkambule, L. L., Sanchis-Juan, A., Singer-Berk, M., Talkowski, M. E., VanNoy, G., van der Merwe, C., NeuroDev Project, Newton, C., O'Donnell-Luria, A., Abubakar, A., Donald, K. A., Robinson, E. B. 2023

    Abstract

    Genetic association studies have made significant contributions to our understanding of the etiology of neurodevelopmental disorders (NDDs). However, these studies rarely focused on the African continent. The NeuroDev Project aims to address this diversity gap through detailed phenotypic and genetic characterization of children with NDDs from Kenya and South Africa. We present results from NeuroDev's first year of data collection, including phenotype data from 206 cases and clinical genetic analyses of 99 parent-child trios. Most cases met criteria for global developmental delay/intellectual disability (GDD/ID, 80.3%). Approximately half of the children with GDD/ID also met criteria for autism. Analysis of exome-sequencing data identified a pathogenic or likely pathogenic variant in 13 (17%) of the 75 cases from South Africa and 9 (38%) of the 24 cases from Kenya. Data from the trio pilot are publicly available, and the NeuroDev Project will continue to develop resources for the global genetics community.

    View details for DOI 10.1016/j.neuron.2023.06.010

    View details for PubMedID 37463579

  • THE NEURODEV PROJECT: PHENOTYPIC AND GENETIC CHARACTERIZATION OF NEURODEVELOPMENTAL DISORDERS IN KENYA AND SOUTH AFRICA Kim, H., Kipkemoi, P., O'Heir, E., Eastman, E., Christ, B., Melly, B., van der Merwe, C., Newton, C., O'Donnell-Luria, A., Abubakar, A., Donald, K. A., Robinson, E. ELSEVIER. 2022: E149

    View details for DOI 10.1016/j.euroneuro.2022.07.275

    View details for Web of Science ID 000898874200049

  • Cognitive test scores vary with choice of personal digital device BEHAVIOR RESEARCH METHODS Passell, E., Strong, R. W., Rutter, L. A., Kim, H., Scheuer, L., Martini, P., Grinspoon, L., Germine, L. 2021; 53 (6): 2544-2557

    Abstract

    Mobile- and web-based psychological research are a valuable addition to the set of tools available for scientific study, reducing logistical barriers for research participation and allowing the recruitment of larger and more diverse participant groups. However, this comes at the cost of reduced control over the technology used by participants, which can introduce new sources of variability into study results. In this study, we examined differences in measured performance on timed and untimed cognitive tests between users of common digital devices in 59,587 (Study 1) and 3818 (Study 2) visitors to TestMyBrain.org , a web-based cognitive testing platform. Controlling for age, gender, educational background, and cognitive performance on an untimed vocabulary test, users of mobile devices, particularly Android smartphones, showed significantly slower performance on tests of reaction time than users of laptop and desktop computers, suggesting that differences in device latency affect measured reaction times. Users of devices that differ in user interface (e.g. screen size, mouse vs. touchscreen) also show significant differences (p < 0.001) in measured performance on tests requiring fast reactions or fine motor movements. By quantifying the contribution of device differences to measured cognitive performance in an online setting, we hope to improve the accuracy of mobile- and web-based cognitive assessments, allowing these methods to be used more effectively.

    View details for DOI 10.3758/s13428-021-01597-3

    View details for Web of Science ID 000647500300001

    View details for PubMedID 33954913

    View details for PubMedCentralID PMC8568735

  • Cross-Disorder Genetic Data Analysis Elucidates a Genetic Link Between Osteoarthritis and Major Depression Lee, P., Barrowsky, S., Jung, J., Nesbit, N., Kim, H., Silberstein, M., Smoller, J. W., Loggia, M. L., Fava, M. ELSEVIER SCIENCE INC. 2021: S144

    View details for Web of Science ID 000645683800347