The DOI matches its Crossref record; 96 of the 96 references it cites were found in a registry or an index.
Allele-specific open chromatin in human iPSC neurons elucidates functional disease variants
Open accessAbstract
Effects of allele-specific open chromatin: Genetic variants in noncoding regions of the genome may underlie the development of disease. However, we are just beginning to tease apart the function of such variants associated with neuropsychiatric disease. Using five types of neural progenitor cells derived from 20 human induced pluripotent stem cell lines, Zhang et al. looked at allele-specific open chromatin (ASoC) variants. Many ASoC variants overlapped with genomic elements, such as transcription factor binding sites, and loci identified in genome-wide association studies for neurological traits. From the experimental and computational analyses, they identified single-nucleotide polymorphisms and illuminate how one schizophrenia-associated variant affects neurodevelopment. Science , this issue p. 561
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“eSNP-karyotyping was performed for all cell lines used to eliminate potential chromosomal abnormalities, as previously described20,21.”
From PICALM Alzheimer’s risk allele causes aberrant lipid droplets in microglia (2025) · cites this paper as [20]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010) · Genome Research · doi:10.1101/gr.107524.110 · Cited by 27,895
Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., Cheng, J. X., Murre, C., Singh, H., & Glass, C. K. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.05.004 · Cited by 13,382
Genome engineering using the CRISPR-Cas9 system
Ran, F. A., Hsu, P. D., Wright, J., Agarwala, V., Scott, D. A., & Zhang, F. (2013) · Nature Protocols · doi:10.1038/nprot.2013.143 · Cited by 11,133
Near-optimal probabilistic RNA-seq quantification
Bray, N. L., Pimentel, H., Melsted, P., & Pachter, L. (2016) · Nature Biotechnology · doi:10.1038/nbt.3519 · Cited by 9,723
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
Biological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368
Mendelian randomization: genetic anchors for causal inference in epidemiological studies
Davey Smith, G., & Hemani, G. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu328 · Cited by 4,677
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534
Self-citationGREAT improves functional interpretation of cis-regulatory regions
McLean, C. Y., Bristor, D., Hiller, M., Clarke, S. L., Schaar, B. T., Lowe, C. B., Wenger, A. M., & Bejerano, G. (2010) · Nature Biotechnology · doi:10.1038/nbt.1630 · Cited by 4,502
Flagged first, then by citations
Cited by
Sorted by citations
Items 101–128 of 128
Single-cell multiomics of neuron activation reveals context-specific genetics of brain disordersPreprint
Liang, L., Zhang, S., Wang, Z., Zhang, H., Li, C., Thapa, C., Oh, E. K., Sirkin, D., Sun, X., Barishman, A., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.17.638682 · Cited by 1
Self-citationThapa, C., Oh, E., Sirkin, D., Lahey, J., de León‐Guerrero, S. D., McCarroll, A., Gowda, P., Zhang, H., Barishman, A., Peyton, L., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.27.708613 · Cited by 1
Self-citationBurgess, D. J. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-00281-0
Detecting isoform-level allelic imbalance accounting for inferential uncertaintyPreprint
Wu, E. Y., Singh, N. P., Choi, K., Zakeri, M., Vincent, M., Churchill, G., Ackert-Bicknell, C. L., Patro, R., & Love, M. (2022) · bioRxiv · doi:10.1101/2022.08.12.503785 · Cited by 3
Zhang, X., Ward, T., Leung, L. C., Qu, P.-P., Zhou, B., Muench, K. L., Khechaduri, A., Plastini, M. J., Charlton, C. A., Pattni, R., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-3152672/v1
Sudwarts, A., Ramesha, S., Gao, T., Ponnusamy, M., Wang, S., Hansen, M. T., Kozlova, A., Bitarafan, S., Kumar, P., Beaulieu‐Abdelahad, D., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22609114
Self-citationTian, W., Dong, S.-S., Jiang, F., Zhang, J.-Q., Wang, C., He, C.-Y., Hu, S.-Y., Hao, R.-H., Song, H., Gao, H.-W., et al. (2024) · bioRxiv · doi:10.1101/2024.06.11.598401
Kanno, S., Sato, K., & Nakazawa, T. (2024) · BIO-PROTOCOL · doi:10.21769/bioprotoc.5191
Li, Q., Gai, Y., Li, Z., Wang, Z., Li, X., Wen, W., & Zhao, C. (2025) · Molecular Neurobiology · doi:10.1007/s12035-025-05469-1
Sudwarts, A., Ramesha, S., Gao, T., Ponnusamy, M., Wang, S., Hansen, M. T., Kozlova, A., Bitarafan, S., Kumar, P., Beaulieu‐Abdelahad, D., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19728376
Self-citationSudwarts, A., Ramesha, S., Gao, T., Ponnusamy, M., Wang, S., Hansen, M. T., Kozlova, A., Bitarafan, S., Kumar, P., Beaulieu‐Abdelahad, D., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19728382
Self-citationSudwarts, A., Ramesha, S., Gao, T., Ponnusamy, M., Wang, S., Hansen, M. T., Kozlova, A., Bitarafan, S., Kumar, P., Beaulieu‐Abdelahad, D., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19728391
Self-citationSudwarts, A., Ramesha, S., Gao, T., Ponnusamy, M., Wang, S., Hansen, M. T., Kozlova, A., Bitarafan, S., Kumar, P., Beaulieu‐Abdelahad, D., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19728373
Self-citationYe, J., Huang, Z., Li, Q., Li, Z., Lan, Y., Wang, Z., Ni, C., Wu, X., Jiang, T., Li, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26652330
Ye, J., Huang, Z., Li, Q., Li, Z., Lan, Y., Wang, Z., Ni, C., Wu, X., Jiang, T., Li, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26652333
Sudwarts, A., Ramesha, S., Gao, T., Ponnusamy, M., Wang, S., Hansen, M. T., Kozlova, A., Bitarafan, S., Kumar, P., Beaulieu‐Abdelahad, D., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19728388
Self-citationWu, E. Y., Singh, N. P., Choi, K., Zakeri, M., Vincent, M. J., Churchill, G. A., Ackert‐Bicknell, C. L., Patro, R., & Love, M. I. (2024) · Figshare · doi:10.6084/m9.figshare.26603722
Clay, S. M., Schoettler, N., Goldstein, A. M., Carbonetto, P. S., Dapas, M., Altman, M. C., Rosasco, M. G., Gern, J. E., Jackson, D. J., Im, H. K., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19845847
Wu, E. Y., Singh, N. P., Choi, K., Zakeri, M., Vincent, M. J., Churchill, G. A., Ackert‐Bicknell, C. L., Patro, R., & Love, M. I. (2024) · Figshare · doi:10.6084/m9.figshare.26603719
Sudwarts, A., Ramesha, S., Gao, T., Ponnusamy, M., Wang, S., Hansen, M. T., Kozlova, A., Bitarafan, S., Kumar, P., Beaulieu‐Abdelahad, D., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19728385
Self-citationSudwarts, A., Ramesha, S., Gao, T., Ponnusamy, M., Wang, S., Hansen, M. T., Kozlova, A., Bitarafan, S., Kumar, P., Beaulieu‐Abdelahad, D., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19728379
Self-citationSudwarts, A., Ramesha, S., Gao, T., Ponnusamy, M., Wang, S., Hansen, M. T., Kozlova, A., Bitarafan, S., Kumar, P., Beaulieu‐Abdelahad, D., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19728370
Self-citationSudwarts, A., Ramesha, S., Gao, T., Ponnusamy, M., Wang, S., Hansen, M. T., Kozlova, A., Bitarafan, S., Kumar, P., Beaulieu‐Abdelahad, D., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19728367
Self-citationXu, Z., Tao, S., Feng, S., Ye, X., Wang, T., Hu, H., Heidrich-O’Hare, E., Chen, W., & Duerr, R. H. (2026) · Nature Communications · doi:10.1038/s41467-026-71383-2
Inferring Gene Regulatory Networks in Stem Cells: Methods and Applications
Solano-Galarza, D., Roeh, S., & Walzthoeni, T. (2026) · Methods in molecular biology · doi:10.1007/978-1-0716-5539-9_1
Hong, Y., Zhao, T., Yang, Q., Zhang, H., Ma, X., Su, X., Liu, J., Zhang, S., Mendez-Maldonado, K., Zhou, Y., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.10.07.756381
Self-citationThapa, C., Oh, E. K., Sirkin, D., Lahey, J., de León-Guerrerro, S. D., McCarroll, A., Gowda, P., Zhang, H.-W., Barishman, A., Peyton, L., et al. (2026) · Stem Cell Reports · doi:10.1016/j.stemcr.2026.103120
Self-citationBrennand, K. (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.19457278
Metadata
- Authors
- Zhang, S., Zhang, H., Zhou, Y., Qiao, M., Zhao, S., Kozlova, A., Shi, J., Sanders, A. R., Wang, G., Luo, K., Sengupta, S., West, S., Qian, S., Streit, M., Avramopoulos, D., Cowan, C. A., Chen, M., Pang, Z. P., Gejman, P. V., He, X., & Duan, J.
- Affiliations
- Endeavor Health (US)
- University of Chicago (US)
- National Cancer Institute (US)
- Johns Hopkins University (US)
- Harvard University (US)
- Rutgers, The State University of New Jersey (US)
- Corresponding author
- Zhang, Siwei
- Zhang, Hanwen
- Zhou, Yifan
- Qiao, Min
- Zhao, Siming
- He, Xin
- Duan, Jubao
- ORCID
- Venue
- Science
- Published
- 2020-07-31
- Volume
- 369
- Issue
- 6503
- Pages
- 561-565
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC7773145
- OpenAlex
- W3046891017
- Cited by
- 127
- References
- 88
- Citations by year
- 2026: 13 · 2025: 14 · 2024: 17 · 2023: 25 · 2022: 30 · 2021: 20 · 2020: 8
- FWCI
- 6.81
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH Office of the Director (R01MH106575, R01MH116281, R01AG063175, R01MH110531, R01AA023797, R01MH113215)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Keywords
- non-coding variants, chromatin accessibility, iPSC-derived neurons, brain development, transcription factor binding, enhancers, expression quantitative trait loci, chromatin interactions
- MeSH terms
- Alleles, Brain, Chromatin, Enhancer Elements, Genetic, Humans, Risk, Schizophrenia, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Induced Pluripotent Stem Cells
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review