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A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes
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Abstract
Environmental cues influence the highly dynamic morphology of microglia. Strategies to characterize these changes usually involve user-selected morphometric features, which preclude the identification of a spectrum of context-dependent morphological phenotypes. Here we develop MorphOMICs, a topological data analysis approach, which enables semiautomatic mapping of microglial morphology into an atlas of cue-dependent phenotypes and overcomes feature-selection biases and biological variability. We extract spatially heterogeneous and sexually dimorphic morphological phenotypes for seven adult mouse brain regions. This sex-specific phenotype declines with maturation but increases over the disease trajectories in two neurodegeneration mouse models, with females showing a faster morphological shift in affected brain regions. Remarkably, microglia morphologies reflect an adaptation upon repeated exposure to ketamine anesthesia and do not recover to control morphologies. Finally, we demonstrate that both long primary processes and short terminal processes provide distinct insights to morphological phenotypes. MorphOMICs opens a new perspective to characterize microglial morphology.
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“Cells portraying smaller cellular somas in addition to extensive and well-branched processes are usually linked to a surveillant state of microglia, whereas the shrinkage of processes and bigger somas are usually linked to reactive states [83–86].”
From Sex chromosomes and sex hormones differently shape microglial properties during normal physiological conditions in the adult mouse hippocampus (2025) · cites this paper as [84]
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Cites
UMAP: Uniform Manifold Approximation and Projection
McInnes, L., Healy, J., Saul, N., & Großberger, L. (2018) · Journal of Open Source Software · doi:10.21105/joss.00861 · Cited by 9,826
Shrestha, S., & Offer, S. M. (2016) · Medical Epigenetics · doi:10.1159/000444713 · Cited by 8,951
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
McInnes, L., Healy, J., & Melville, J. (2018) · arXiv · doi:10.48550/arxiv.1802.03426 · Cited by 7,101
Resting microglial cells are highly dynamic surveillants of brain parenchyma in vivo
Nimmerjahn, A., Kirchhoff, F., & Helmchen, F. (2005) · Science · doi:10.1126/science.1110647 · Cited by 5,827
Genome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572
Fate Mapping Analysis Reveals That Adult Microglia Derive from Primitive Macrophages
Ginhoux, F., Greter, M., Leboeuf, M., Nandi, S., See, P., Gokhan, S., Mehler, M. F., Conway, S. J., Ng, L. G., Stanley, E. R., et al. (2010) · Science · doi:10.1126/science.1194637 · Cited by 5,175
The single-cell transcriptional landscape of mammalian organogenesis
Cao, J., Spielmann, M., Qiu, X., Huang, X., Ibrahim, D. M., Hill, A. J., Zhang, F., Mundlos, S., Christiansen, L., Steemers, F. J., et al. (2019) · Nature · doi:10.1038/s41586-019-0969-x · Cited by 4,490
Synaptic Pruning by Microglia Is Necessary for Normal Brain Development
Paolicelli, R. C., Bolasco, G., Pagani, F., Maggi, L., Scianni, M., Panzanelli, P., Giustetto, M., Ferreira, T. A., Guiducci, E., Dumas, L., et al. (2011) · Science · doi:10.1126/science.1202529 · Cited by 4,244
Host microbiota constantly control maturation and function of microglia in the CNS
Erny, D., Hrabě de Angelis, A. L., Jaitin, D., Wieghofer, P., Staszewski, O., David, E., Keren-Shaul, H., Mahlakoiv, T., Jakobshagen, K., Buch, T., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4030 · Cited by 3,569
Research works printed but not linked: 1
- Van Der Maaten, L. & Hinton, G. Visualizing data using t-SNE. J. Mach. Learn. Res. 9, 2579–2605 (2008).
Cited by
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Paolicelli, R. C., Sierra, A., Stevens, B., Tremblay, M.-E., Aguzzi, A., Ajami, B., Amit, I., Audinat, E., Bechmann, I., Bennett, M., et al. (2022) · Neuron · doi:10.1016/j.neuron.2022.10.020 · Cited by 1,973
Self-citationHuman microglial state dynamics in Alzheimer’s disease progression
Sun, N., Victor, M. B., Park, Y. P., Xiong, X., Scannail, A. N., Leary, N., Prosper, S., Viswanathan, S., Luna, X., Boix, C. A., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.037 · Cited by 462
Self-citationMicroglial morphometric analysis: so many options, so little consistency
Reddaway, J., Richardson, P., Bevan, R. J., Stoneman, J., & Palombo, M. (2023) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2023.1211188 · Cited by 131
Quantifying microglial morphology: an insight into function
Green, T. R. F., & Rowe, R. K. (2024) · Clinical & Experimental Immunology · doi:10.1093/cei/uxae023 · Cited by 119
Müller, L., Benedetto, S. D., & Müller, V. (2025) · Cells · doi:10.3390/cells14010054 · Cited by 102
Kim, J. S., Pavlidis, P., & Ciernia, A. V. (2024) · eNeuro · doi:10.1523/eneuro.0014-24.2024 · Cited by 64
Johnson, N. R., Yuan, P., Castillo, E., Lopez, T. P., Yue, W., Bond, A., Rivera, B. M., Sullivan, M. C., Hirouchi, M., Giles, K., et al. (2023) · Nature Communications · doi:10.1038/s41467-022-35753-w · Cited by 46
Lewy body dementia promotion by air pollutants
Zhang, X., Liu, H., Wu, X., Jia, L., Gadhave, K., Wang, L., Zhang, K., Li, H., Chen, R., Kumbhar, R., et al. (2025) · Science · doi:10.1126/science.adu4132 · Cited by 48
Bobotis, B. C., Braniff, O., Gargus, M., Akinluyi, E. T., Awogbindin, I. O., & Tremblay, M.-È. (2023) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2023.110752 · Cited by 40
The dual nature of neuroinflammation in networked brain
Müller, L., Benedetto, S. D., & Müller, V. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1659947 · Cited by 43
Online conversion of reconstructed neural morphologies into standardized SWC format
Mehta, K., Ljungquist, B., Ogden, J., Nanda, S., Ascoli, R., Ng, L., & Ascoli, G. A. (2023) · Nature Communications · doi:10.1038/s41467-023-42931-x · Cited by 23
van Weering, H. R. J., Nijboer, T. W., Brummer, M. L., Boddeke, E., & Eggen, B. J. L. (2023) · Glia · doi:10.1002/glia.24427 · Cited by 26
Relationship between sex biases in gene expression and sex biases in autism and Alzheimer’s disease
Fass, S. B., Mulvey, B., Chase, R., Yang, W. C., Selmanovic, D., Chaturvedi, S. M., Tycksen, E., Weiss, L. A., & Dougherty, J. D. (2024) · Biology of Sex Differences · doi:10.1186/s13293-024-00622-2 · Cited by 25
Sheridan, S. D., Horng, J. E., Yeh, H., McCrea, L. T., Wang, J. P., Fu, T., & Perlis, R. H. (2022) · Biological Psychiatry · doi:10.1016/j.biopsych.2023.07.022 · Cited by 19
Type I interferon signalling and interferon‐responsive microglia in health and disease
López‐Atalaya, J. P., & Bhojwani-Cabrera, A. M. (2025) · FEBS Journal · doi:10.1111/febs.70126 · Cited by 23
Bobotis, B. C., Khakpour, M., Braniff, O., de Andrade, E. G., Gargus, M., Allen, M., Carrier, M., Baillargeon, J., Rangachari, M., & Tremblay, M.-È. (2025) · Journal of Neuroinflammation · doi:10.1186/s12974-025-03341-6 · Cited by 17
“This analysis provides insight into microglial function across contexts of health and disease [57, 84].”
Regulation of disease-associated microglia in the optic nerve by lipoxin B4 and ocular hypertension
Maurya, S., Lin, M., Karnam, S., Singh, T., Kumar, M., Ward, E., Sivak, J. M., Flanagan, J. G., & Gronert, K. (2024) · Molecular Neurodegeneration · doi:10.1186/s13024-024-00775-z · Cited by 17
Shi, L., Liu, S., Chen, J., Wang, H., & Wang, Z. (2024) · Neural Regeneration Research · doi:10.4103/nrr.nrr-d-24-00810 · Cited by 15
Le, L., Eliseeva, S. I., Plunk, E. C., Kara-Pabani, K., Li, H., Yarovinsky, F., & Majewska, A. K. (2025) · Cell Reports · doi:10.1016/j.celrep.2024.115176 · Cited by 13
Sanchez-Molina, P., Rosmus, D.-D., Brownell, D., Meral, M., Gohlich, C., Pratapa, A., Peymanfar, Y., Whitley, A., Hou, Y., Nikulina, N., et al. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02267-3 · Cited by 21
Dong, M., Qian, Y., Geng, Y., Wang, R., Wang, Y., Cai, J., Wang, X., Huang, Y., Liu, Y., Liu, W., et al. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251378007 · Cited by 12
Microglia contribute to cognitive decline in hypercholesterolemic LDLr −/− mice
Rodrigues, M. S., do Nascimento, N. B., Farias, H. R., Schons, T., Machado, A. G., Medeiros, E. B., Mesquita, A., Bast, R. K., Budni, J., Engblom, D., et al. (2023) · Journal of Neurochemistry · doi:10.1111/jnc.15952 · Cited by 13
Uweru, J. O., Okojie, A. K., Trivedi, A., Benderoth, J., Thomas, L. S., Davidson, G. K., Cox, K., & Eyo, U. B. (2024) · Journal of Neuroinflammation · doi:10.1186/s12974-024-03079-7 · Cited by 11
Maksour, S., & Ooi, L. (2023) · Journal of Neurochemistry · doi:10.1111/jnc.15885 · Cited by 12
Microglia role as the regulator of cognitive function
Sousa, R. A. L. D., & Cassilhas, R. C. (2023) · Revista da Associação Médica Brasileira · doi:10.1590/1806-9282.20230412 · Cited by 11
Cell morphologies in the nervous system: Glia steal the limelight
Ascoli, G. A. (2022) · The Journal of Comparative Neurology · doi:10.1002/cne.25429 · Cited by 9
Maes, M. E., Colombo, G., Uiterkamp, F. E. S., Sternberg, F., Venturino, A., Pohl, E. E., & Siegert, S. (2023) · iScience · doi:10.1016/j.isci.2023.107780 · Cited by 9
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Wurl, J. A., Nair, C. E. M., Dietz, J. A., Shestopalov, V. I., & Nickells, R. W. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms242115641 · Cited by 9
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VonKaenel, E. D., Feidler, A. M., Lowery, R. L., Andersh, K. M., Love, T., Majewska, A. K., & McCall, M. N. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae156 · Cited by 8
Zhang, Y., & Tang, C. (2024) · Aging and Disease · doi:10.14336/ad.2024.0326 · Cited by 7
Perochon, T., Krsnik, Ž., Massimo, M., Ruchiy, Y., Romero, A. L., Mohammadi, E., Li, X., Long, K. R., Parkkinen, L., Blomgren, K., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56560-z · Cited by 7
Ward, E., Benowitz, L. I., Brunner, T. M., Bu, G., Cayouette, M., Canto-Soler, V., Mesquita, S. D., Polo, A. D., DiAntonio, A., Duan, X., et al. (2025) · Molecular Neurodegeneration · doi:10.1186/s13024-025-00858-5 · Cited by 7
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Fitzgerald, E., Pokhvisneva, I., Patel, S. H., Chan, S. Y., Tan, A. P., Chen, H., Silveira, P. P., & Meaney, M. J. (2024) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2024.04.030 · Cited by 5
Johnson, N. R., Yuan, P., Castillo, E., Lopez, T. P., Yue, W., Bond, A., Rivera, B. M., Sullivan, M. C., Hirouchi, M., Giles, K., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.20.436288 · Cited by 5
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Cserép, C., Berki, P., Mars, M., Pósfai, B., Pasterkamp, R. J., Benkő, S., & Dénes, Á. (2025) · Trends in Neurosciences · doi:10.1016/j.tins.2025.10.004 · Cited by 5
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Maya-Arteaga, J. P., Martínez-Orozco, H., & Díaz-Cintra, S. Y. (2024) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2024.1505048 · Cited by 6
Birkle, T. J. Y., Willems, H. M. G., Skidmore, J., & Brown, G. C. (2024) · iScience · doi:10.1016/j.isci.2024.109454 · Cited by 4
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Taborda-Bejarano, J. P., Nowak, D. B., Chaure, F. J., Allen, M. L., Blek, K. A., Walterhouse, S. H., Mantsch, J. R., & García‐Keller, C. (2025) · Cells · doi:10.3390/cells14171354 · Cited by 3
Benkeder, S., Dinh, S.-M., Marchal, P., Gea, P. D., Thoby‐Brisson, M., Hubert, V., Hristovska, I., Pitollat, G., Combet, K., Cardoit, L., et al. (2024) · eLife · doi:10.1101/2024.08.29.609024 · Cited by 3
Matoba, K., Kochi, T., Mreyoud, Y., Badrani, J. H., Patel, H., Tsujioka, H., Yamashita, T., Crossman, D. K., Niwa, M., & Kano, S. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.19.609743 · Cited by 3
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Bonilla, M. I., Lee, H.-L., Foster, S., Kim, I.-J., & Rudenko, A. (2025) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2025.100591 · Cited by 1
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Venturino, A., Alamalhoda, M., Negrello, T., Jin, K., van Velthoven, C. T. J., Cubero, R. J., Yeung, J., Koppensteiner, P., Tasic, B., & Siegert, S. (2026) · Science Advances · doi:10.1126/sciadv.adz6517 · Cited by 1
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Du, J. T., Chartrand, T., Jayadev, S., Prater, K. E., & Lin, K. (2026) · Journal of Computational Biology · doi:10.1177/15578666261492321 · Cited by 2
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Maes, M. E., Colombo, G., Uiterkamp, F. E. S., Sternberg, F., Venturino, A., Pohl, E. E., & Siegert, S. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.22.504738
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Uweru, J. O., Okojie, K. A., Trivedi, A., Benderoth, J., Thomas, L. S., Davidson, G. K., Cox, K., & Eyo, U. B. (2024) · Research Square · doi:10.21203/rs.3.rs-3997803/v1
Maurya, S., Lin, M., Karnam, S., Singh, T., Kumar, M., Ward, E., Sivak, J. M., Flanagan, J. G., & Gronert, K. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.03.18.585452
Le, L., Eliseeva, S. I., Kara-Pabani, K., Li, H., Yarovinsky, F., & Majewska, A. K. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4795163
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Eperon, A., Doeller, C. F., Theves, S., & Bottini, R. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.01.21.633955
Benkeder, S., Dinh, S.-M., Marchal, P., Gea, P. D., Thoby‐Brisson, M., Hubert, V., Hristovska, I., Pitollat, G., Combet, K., Cardoit, L., et al. (2025) · eLife · doi:10.7554/elife.101630.2
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Fass, S. B., Mulvey, B., Chase, R., Yang, W., Selmanovic, D., Chaturvedi, S. M., Tycksen, E., Weiss, L. A., & Dougherty, J. D. (2024) · Figshare · doi:10.6084/m9.figshare.26730706
Fass, S. B., Mulvey, B., Chase, R., Yang, W., Selmanovic, D., Chaturvedi, S. M., Tycksen, E., Weiss, L. A., & Dougherty, J. D. (2024) · Figshare · doi:10.6084/m9.figshare.26730724
Fass, S. B., Mulvey, B., Chase, R., Yang, W., Selmanovic, D., Chaturvedi, S. M., Tycksen, E., Weiss, L. A., & Dougherty, J. D. (2024) · Figshare · doi:10.6084/m9.figshare.26730709
Fass, S. B., Mulvey, B., Chase, R., Yang, W., Selmanovic, D., Chaturvedi, S. M., Tycksen, E., Weiss, L. A., & Dougherty, J. D. (2024) · Figshare · doi:10.6084/m9.figshare.26730715
Fass, S. B., Mulvey, B., Chase, R., Yang, W., Selmanovic, D., Chaturvedi, S. M., Tycksen, E., Weiss, L. A., & Dougherty, J. D. (2024) · Figshare · doi:10.6084/m9.figshare.26730730
Fass, S. B., Mulvey, B., Chase, R., Yang, W., Selmanovic, D., Chaturvedi, S. M., Tycksen, E., Weiss, L. A., & Dougherty, J. D. (2024) · Figshare · doi:10.6084/m9.figshare.26730718
Uweru, J. O., Okojie, A. K., Trivedi, A., Benderoth, J., Thomas, L. S., Davidson, G. K., Cox, K., & Eyo, U. B. (2024) · Figshare · doi:10.6084/m9.figshare.25608684
Fass, S. B., Mulvey, B., Chase, R., Yang, W., Selmanovic, D., Chaturvedi, S. M., Tycksen, E., Weiss, L. A., & Dougherty, J. D. (2024) · Figshare · doi:10.6084/m9.figshare.26730721
Uweru, J. O., Okojie, A. K., Trivedi, A., Benderoth, J., Thomas, L. S., Davidson, G. K., Cox, K., & Eyo, U. B. (2024) · Figshare · doi:10.6084/m9.figshare.25608855
Fass, S. B., Mulvey, B., Chase, R., Yang, W., Selmanovic, D., Chaturvedi, S. M., Tycksen, E., Weiss, L. A., & Dougherty, J. D. (2024) · Figshare · doi:10.6084/m9.figshare.26730727
Uweru, J. O., Okojie, A. K., Trivedi, A., Benderoth, J., Thomas, L. S., Davidson, G. K., Cox, K., & Eyo, U. B. (2024) · Figshare · doi:10.6084/m9.figshare.26706972
Uweru, J. O., Okojie, A. K., Trivedi, A., Benderoth, J., Thomas, L. S., Davidson, G. K., Cox, K., & Eyo, U. B. (2024) · Figshare · doi:10.6084/m9.figshare.26706969
Fass, S. B., Mulvey, B., Chase, R., Yang, W., Selmanovic, D., Chaturvedi, S. M., Tycksen, E., Weiss, L. A., & Dougherty, J. D. (2024) · Figshare · doi:10.6084/m9.figshare.26730712
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Manifold learning for personalized and label-free detection of cardiac arrhythmias
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Self-citationXia, Y., Yuan, P., Fei, G., & Cheng, X. (2026) · Brain medicine : · doi:10.61373/bm026y.0051
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Metadata
- Authors
- Colombo, G., Cubero, R. J. A., Kanari, L., Venturino, A., Schulz, R., Scolamiero, M., Agerberg, J., Mathys, H., Tsai, L.-H., Chachólski, W., Hess, K., & Siegert, S.
- Affiliations
- Institute of Science and Technology Austria (AT)
- École Polytechnique Fédérale de Lausanne (CH)
- KTH Royal Institute of Technology (SE)
- Broad Institute (US)
- Corresponding author
- Siegert, Sandra
- ORCID
- Venue
- Nature Neuroscience
- Published
- 2022-09-30
- Volume
- 25
- Issue
- 10
- Pages
- 1379-1393
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC9534764
- OpenAlex
- W4298137907
- Cited by
- 100
- References
- 125
- Citations by year
- 2026: 25 · 2025: 23 · 2024: 31 · 2023: 15 · 2022: 5
- FWCI
- 7.20
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature Neuroscience (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- SDL (submittedVersion)
- Funders
- JPB Foundation
- Institute of Science and Technology Austria (715571, 754411)
- European Commission (HORIZON2020, 754411)
- École Polytechnique Fédérale de Lausanne
- Bundesministerium für Wissenschaft, Forschung und Wirtschaft
- Board of the Swiss Federal Institutes of Technology
- National Institutes of Health
- National Institute of Neurological Disorders and Stroke (R37NS051874)
- H2020 Marie Skłodowska-Curie Actions (754411, HORIZON2020, 715571)
- Topics
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- microglial morphology, morphomics, topological data analysis, sex differences, regional brain differences, microglial phenotype, neurodegeneration, ketamine anesthesia, microglial maturation, mouse brain
- MeSH terms
- Animals, Brain, Disease Models, Animal, Female, Ketamine, Male, Phenotype, Microglia, Mice
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