Fast and accurate metagenotyping of the human gut microbiome with GT-Pro
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Abstract
Single nucleotide polymorphisms (SNPs) in metagenomics are used to quantify population structure, track strains and identify genetic determinants of microbial phenotypes. However, existing alignment-based approaches for metagenomic SNP detection require high-performance computing and enough read coverage to distinguish SNPs from sequencing errors. To address these issues, we developed the GenoTyper for Prokaryotes (GT-Pro), a suite of methods to catalog SNPs from genomes and use unique k-mers to rapidly genotype these SNPs from metagenomes. Compared to methods that use read alignment, GT-Pro is more accurate and two orders of magnitude faster. Using high-quality genomes, we constructed a catalog of 104 million SNPs in 909 human gut species and used unique k-mers targeting this catalog to characterize the global population structure of gut microbes from 7,459 samples. GT-Pro enables fast and memory-efficient metagenotyping of millions of SNPs on a personal computer.
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The advancement of computational tools for shotgun metagenomic sequencing has enabled profiling of microbes taxonomically and quantitatively and access to genetic information at subspecies and strain resolutions.
“The advancement of computational tools for the analysis of shotgun metagenomic sequencing has enabled researchers to not only profile microbes taxonomically and quantitatively but also to access their genetic information at subspecies and strain resolutions.”
From Global genetic diversity of human gut microbiome species is related to geographic location and host health (2025) · cites this paper as [12]
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Cites
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041 · see citing works
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607 · see citing works
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400 · see citing works
RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies
Stamatakis, A. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu033 · Cited by 32,291 · see citing works
BLAST+: architecture and applications
Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., & Madden, T. L. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-421 · Cited by 22,074 · see citing works
Search and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 20,617 · see citing works
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247 · see citing works
Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega
Sievers, F., Wilm, A., Dineen, D., Gibson, T., Karplus, K., Li, W.-Z., Lopez, R., McWilliam, H., Remmert, M., Söding, J., et al. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.75 · Cited by 15,576 · see citing works
Second-generation PLINK: rising to the challenge of larger and richer datasets
Chang, C. C., Chow, C. C., Tellier, L. C., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015) · Gigascience · doi:10.1186/s13742-015-0047-8 · Cited by 12,709 · see citing works
Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P., & Tyson, G. W. (2015) · Genome Research · doi:10.1101/gr.186072.114 · Cited by 12,496 · see citing works
Prodigal: prokaryotic gene recognition and translation initiation site identification
Hyatt, D., Chen, G.-L., LoCascio, P. F., Land, M., Larimer, F. W., & Hauser, L. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-119 · Cited by 12,426 · see citing works
Turnbaugh, P. J., Ley, R. E., Hamady, M., Fraser-Liggett, C. M., Knight, R., & Gordon, J. I. (2007) · Nature · doi:10.1038/nature06244 · Cited by 6,091 · see citing works
Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions.
Nei, M., & Gojobori, T. (1986) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a040410 · Cited by 4,904 · see citing works
Kraken: ultrafast metagenomic sequence classification using exact alignments
Wood, D. E., & Salzberg, S. L. (2014) · Genome Biology · doi:10.1186/gb-2014-15-3-r46 · Cited by 4,521 · see citing works
Olm, M. R., Brown, C. T., Brooks, B., & Banfield, J. F. (2017) · The ISME Journal · doi:10.1038/ismej.2017.126 · Cited by 3,031 · see citing works
Leinonen, R., Sugawara, H., & Shumway, M. F. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1019 · Cited by 2,760 · see citing works
MUMmer4: A fast and versatile genome alignment system
Marçais, G., Delcher, A. L., Phillippy, A. M., Coston, R., Salzberg, S. L., & Zimin, A. (2018) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005944 · Cited by 2,484 · see citing works
Gut microbiome structure and metabolic activity in inflammatory bowel disease
Franzosa, E. A., Sirota-Madi, A., Avila-Pacheco, J., Fornelos, N., Haiser, H. J., Reinker, S., Vatanen, T., Hall, A. B., Mallick, H., McIver, L. J., et al. (2018) · Nature Microbiology · doi:10.1038/s41564-018-0306-4 · Cited by 1,995 · see citing works
Smith, J. M., Smith, N. H., O'Rourke, M., & Spratt, B. G. (1993) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.90.10.4384 · Cited by 1,802 · see citing works
Metagenomic microbial community profiling using unique clade-specific marker genes
Segata, N., Waldron, L., Ballarini, A., Narasimhan, V., Jousson, O., & Huttenhower, C. (2012) · Nature Methods · doi:10.1038/nmeth.2066 · Cited by 1,776 · see citing works
Treangen, T. J., Ondov, B., Koren, S., & Phillippy, A. M. (2014) · Genome biology · doi:10.1186/s13059-014-0524-x · Cited by 1,632 · see citing works
Pasolli, E., Asnicar, F., Manara, S., Zolfo, M., Karcher, N., Armanini, F., Beghini, F., Manghi, P., Tett, A., Ghensi, P., et al. (2019) · Cell · doi:10.1016/j.cell.2019.01.001 · Cited by 1,591 · see citing works
A unified catalog of 204,938 reference genomes from the human gut microbiome
Almeida, A., Nayfach, S., Boland, M., Strozzi, F., Beracochea, M., Shi, Z. J., Pollard, K. S., Sakharova, E., Parks, D. H., Hugenholtz, P., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-0603-3 · Cited by 1,367 · see citing works
A new genomic blueprint of the human gut microbiota
Almeida, A., Mitchell, A. L., Boland, M., Forster, S. C., Gloor, G. B., Tarkowska, A., Lawley, T. D., & Finn, R. D. (2019) · Nature · doi:10.1038/s41586-019-0965-1 · Cited by 1,314 · see citing works
Genomic variation landscape of the human gut microbiome
Schloissnig, S., Arumugam, M., Sunagawa, S., Mitreva, M., Tap, J., Zhu, A., Waller, A., Mende, D. R., Kultima, J. R., Martin, J., et al. (2013) · Nature · doi:10.1038/nature11711 · Cited by 907 · see citing works
Seasonal cycling in the gut microbiome of the Hadza hunter-gatherers of Tanzania
Smits, S. A., Leach, J., Sonnenburg, E. D., Gonzalez, C. G., Lichtman, J. S., Reid, G., Knight, R., Manjurano, A., Changalucha, J., Elias, J. E., et al. (2017) · Science · doi:10.1126/science.aan4834 · Cited by 886 · see citing works
Microbial strain-level population structure and genetic diversity from metagenomes
Truong, D. T., Tett, A., Pasolli, E., Huttenhower, C., & Segata, N. (2017) · Genome Research · doi:10.1101/gr.216242.116 · Cited by 839 · see citing works
Discovery and inhibition of an interspecies gut bacterial pathway for Levodopa metabolism
Maini Rekdal, V., Bess, E. N., Bisanz, J. E., Turnbaugh, P. J., & Balskus, E. P. (2019) · Science · doi:10.1126/science.aau6323 · Cited by 753 · see citing works
Dynamics and stabilization of the human gut microbiome during the first year of life
Bäckhed, F., Roswall, J., Peng, Y., Feng, Q., Jia, H., Kovatcheva-Datchary, P., Li, Y., Xia, Y., Xie, H., Zhong, H., et al. (2015) · Cell Host & Microbe · doi:10.1016/j.chom.2015.05.012 · Cited by 738 · see citing works
New insights from uncultivated genomes of the global human gut microbiome
Nayfach, S., Shi, Z. J., Seshadri, R., Pollard, K. S., & Kyrpides, N. C. (2019) · Nature · doi:10.1038/s41586-019-1058-x · Cited by 737 · see citing works
KMC 3: counting and manipulating k‐mer statistics
Kokot, M., Dlugosz, M., & Deorowicz, S. (2017) · Bioinform. · doi:10.1093/bioinformatics/btx304 · Cited by 720 · see citing works
Ounit, R., Wanamaker, S. I., Close, T. J., & Lonardi, S. (2015) · BMC Genomics · doi:10.1186/s12864-015-1419-2 · Cited by 624 · see citing works
1,520 reference genomes from cultivated human gut bacteria enable functional microbiome analyses
Zou, Y., Xue, W., Luo, G., Deng, Z., Qin, P., Guo, R., Sun, H., Xia, Y., Liang, S., Dai, Y., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-018-0008-8 · Cited by 526 · see citing works
KrakenUniq: confident and fast metagenomics classification using unique k-mer counts
Breitwieser, F. P., Baker, D. N., & Salzberg, S. L. (2018) · Genome biology · doi:10.1186/s13059-018-1568-0 · Cited by 480 · see citing works
Nayfach, S., Rodriguez-Mueller, B., Garud, N., & Pollard, K. S. (2016) · Genome Research · doi:10.1101/gr.201863.115 · Cited by 470 · see citing works
Self-citationThe Landscape of Genetic Content in the Gut and Oral Human Microbiome
Tierney, B. T., Yang, Z., Luber, J. M., Beaudin, M., Wibowo, M. C., Baek, C., Mehlenbacher, E., Patel, C. J., & Kostic, A. D. (2019) · Cell Host & Microbe · doi:10.1016/j.chom.2019.07.008 · Cited by 348 · see citing works
Evolutionary dynamics of bacteria in the gut microbiome within and across hosts
Garud, N. R., Good, B. H., Hallatschek, O., & Pollard, K. S. (2019) · PLoS Biology · doi:10.1371/journal.pbio.3000102 · Cited by 347 · see citing works
Accurate and universal delineation of prokaryotic species
Mende, D. R., Sunagawa, S., Zeller, G., & Peer Bork, B. (2013) · Nature Methods · doi:10.1038/nmeth.2575 · Cited by 328 · see citing works
ConStrains identifies microbial strains in metagenomic datasets
Luo, C., Knight, R. D., Siljander, H., Knip, M., Xavier, R. J., & Gevers, D. (2015) · Nature Biotechnology · doi:10.1038/nbt.3319 · Cited by 267 · see citing works
Clostridium difficile and inflammatory bowel disease
Issa, M., Ananthakrishnan, A. N., & Binion, D. G. (2008) · Inflammatory Bowel Diseases · doi:10.1002/ibd.20500 · Cited by 253 · see citing works
Simulating Illumina metagenomic data with InSilicoSeq
Gourlé, H., Lindsjö, O. K., Hayer, J., & Bongcam‐Rudloff, E. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty630 · Cited by 243 · see citing works
Redfield, R. J. (2001) · Nature Reviews Genetics · doi:10.1038/35084593 · Cited by 230 · see citing works
MOCAT: A Metagenomics Assembly and Gene Prediction Toolkit
Kultima, J. R., Sunagawa, S., Li, J., Chen, W., Chen, H., Mende, D. R., Arumugam, M., Pan, Q., Liu, B., Qin, J., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0047656 · Cited by 199 · see citing works
DESMAN: a new tool for de novo extraction of strains from metagenomes
Quince, C., Delmont, T., Raguideau, S., Alneberg, J., Darling, A., Collins, G., & Eren, A. (2017) · Genome Biology · doi:10.1186/s13059-017-1309-9 · Cited by 175 · see citing works
Rousseau, C., Levenez, F., Fouqueray, C., Dore, J. M., Collignon, A., & Lepage, P. (2010) · Journal of Clinical Microbiology · doi:10.1128/jcm.01507-10 · Cited by 138 · see citing works
Population Genetics in the Human Microbiome
Garud, N. R., & Pollard, K. S. (2019) · Trends in Genetics · doi:10.1016/j.tig.2019.10.010 · Cited by 137 · see citing works
Vincent, C., Miller, M. A., Edens, T. J., Mehrotra, S., Dewar, K., & Manges, A. R. (2016) · Microbiome · doi:10.1186/s40168-016-0156-3 · Cited by 124 · see citing works
metaSNV: A tool for metagenomic strain level analysis
Costea, P. I., Munch, R., Coelho, L. P., Paoli, L., Sunagawa, S., & Bork, P. (2017) · PLoS ONE · doi:10.1371/journal.pone.0182392 · Cited by 103 · see citing works
Chattopadhyay, S., Weissman, S. J., Minin, V. N., Russo, T. A., Dykhuizen, D. E., & Sokurenko, E. V. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0906217106 · Cited by 99 · see citing works
Impacts of florfenicol on the microbiota landscape and resistome as revealed by metagenomic analysis
Zeng, Q., Liao, C., Terhune, J. S., & Wang, L. (2019) · Microbiome · doi:10.1186/s40168-019-0773-8 · Cited by 90 · see citing works
Inferring bacterial recombination rates from large-scale sequencing datasets
Lin, M., & Kussell, E. L. (2019) · Nature Methods · doi:10.1038/s41592-018-0293-7 · Cited by 82 · see citing works
Impact of Homologous Recombination on the Evolution of Prokaryotic Core Genomes
González‐Torres, P., Rodríguez, F., Antón, J., & Gabaldón, T. (2019) · mBio · doi:10.1128/mbio.02494-18 · Cited by 81 · see citing works
Comprehensive DNA Signature Discovery and Validation
Phillippy, A. M., Mason, J. A., Ayanbule, K., Sommer, D. D., Taviani, E., Huq, A., Colwell, R. R., Knight, I. T., & Salzberg, S. L. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030098 · Cited by 78 · see citing works
Fast genotyping of known SNPs through approximate k -mer matching
Shajii, A., Yörükoğlu, D., Yu, Y. W., & Berger, B. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw460 · Cited by 61 · see citing works
Inference of the Properties of the Recombination Process from Whole Bacterial Genomes
Ansari, M. A., & Didelot, X. (2013) · Genetics · doi:10.1534/genetics.113.157172 · Cited by 47 · see citing works
Liu, X., Yu, Y., Liu, J., Elliott, C. F., Qian, C., & Liu, J. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx432 · Cited by 39 · see citing works
Liu, Y., Zhang, L. Y., & Li, J. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz273 · Cited by 23 · see citing works
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Research works printed but not linked: 1
- Almeida, A. et al. A unified sequence catalogue of over 280,000 genomes obtained from the human gut microbiome. bioRxiv 762682 (2019) doi:10.1101/762682. · DOI
Cited by
Sorted by citations
Benchmarking spatial clustering methods with spatially resolved transcriptomics data
Yuan, Z., Zhao, F., Lin, S., Zhao, Y. S., Yao, J., Cui, Y., Zhang, X.-Y., & Zhao, Y. C. (2024) · Nature Methods · doi:10.1038/s41592-024-02215-8 · Cited by 200 · see citing works
Genome-resolved metagenomics: a game changer for microbiome medicine
Kim, N., Ma, J., Kim, W., Kim, J., Belenky, P. A., & Lee, I. (2024) · Experimental & Molecular Medicine · doi:10.1038/s12276-024-01262-7 · Cited by 131 · see citing works
Andreu-Sánchez, S., Blanco-Míguez, A., Wang, D., Golzato, D., Manghi, P., Heidrich, V., Fackelmann, G., Zhernakova, D. V., Kurilshikov, A., Valles-Colomer, M., et al. (2025) · Cell · doi:10.1016/j.cell.2025.04.014 · Cited by 81 · see citing works
Applying multi‐omics toward tumor microbiome research
Zhang, N., Kandalai, S., Zhou, X., Hossain, F., & Zheng, Q. (2023) · iMeta · doi:10.1002/imt2.73 · Cited by 69 · see citing works
Bacterial SNPs in the human gut microbiome associate with host BMI
Zahavi, L., Lavon, A., Reicher, L., Shoer, S., Godneva, A., Leviatan, S., Rein, M., Weissbrod, O., Weinberger, A., & Segal, E. (2023) · Nature Medicine · doi:10.1038/s41591-023-02599-8 · Cited by 58 · see citing works
Smith, B. J., Piceno, Y. M., Zydek, M., Zhang, B., Syriani, L. A., Terdiman, J. P., Kassam, Z., Ma, A. I., Lynch, S. V., Pollard, K. S., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-09307-5 · Cited by 46 · see citing works
Challenges and opportunities of strain diversity in gut microbiome research
Anderson, B., & Bisanz, J. E. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1117122 · Cited by 45 · see citing works
Häcker, D., Siebert, K., Smith, B. J., Koehler, N., Riva, A., Mahapatra, A., Heimes, H., Nie, J., Metwaly, A., Hölz, H., et al. (2024) · Cell Host and Microbe · doi:10.1016/j.chom.2024.10.001 · Cited by 41 · see citing works
Strain Identification and Quantitative Analysis in Microbial Communities
Ghazi, A. R., Münch, P. C., Chen, D., Jensen, J., & Huttenhower, C. (2022) · Journal of Molecular Biology · doi:10.1016/j.jmb.2022.167582 · Cited by 42 · see citing works
The soil-plant-human gut microbiome axis into perspective
Ma, H., Cornadó, D., & Raaijmakers, J. M. (2025) · Nature Communications · doi:10.1038/s41467-025-62989-z · Cited by 38 · see citing works
Dynamics of bacterial recombination in the human gut microbiome
Liu, Z., & Good, B. H. (2024) · PLoS Biology · doi:10.1371/journal.pbio.3002472 · Cited by 34 · see citing works
Wang, D., Yang, X., Ren, Z., Hu, B., Zhao, H., Yang, K., Shi, P., Zhang, Z., Feng, Q., Nawenja, C. V., et al. (2024) · Microbiome · doi:10.1186/s40168-024-01782-4 · Cited by 33 · see citing works
Pitfalls of genotyping microbial communities with rapidly growing genome collections
Zhao, C., Shi, Z. J., & Pollard, K. S. (2023) · Cell Systems · doi:10.1016/j.cels.2022.12.007 · Cited by 29 · see citing works
Cai, J., Auster, A., Cho, S., & Lai, Z. (2023) · Journal of Advanced Research · doi:10.1016/j.jare.2023.07.002 · Cited by 29 · see citing works
Scalable Microbial Strain Inference in Metagenomic Data Using StrainFacts
Smith, B. J., Li, X., Shi, Z. J., Abate, A. R., & Pollard, K. S. (2022) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2022.867386 · Cited by 18 · see citing works
Ma, J., Kim, N., Cha, J. H., Kim, W., Kim, C. Y., Lee, Y.-H., Kim, H., Han, Y. D., Yong, D., Han, E., et al. (2025) · Nature Microbiology · doi:10.1038/s41564-025-02206-1 · Cited by 20 · see citing works
Multi-dimensional metagenomics
Peng, H., Ruiz-Moreno, A. J., & Fu, J. (2025) · Nature Reviews Bioengineering · doi:10.1038/s44222-025-00346-x · Cited by 16 · see citing works
Wang, S., Jiang, Y., Che, L., Wang, R. H., & Li, S. C. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae515 · Cited by 14 · see citing works
Yang, H. K., Cao, B., Tang, J., & Wang, J. (2025) · Frontiers in Microbiology · doi:10.3389/fmicb.2025.1592549 · Cited by 11 · see citing works
Maast: genotyping thousands of microbial strains efficiently
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · Genome biology · doi:10.1186/s13059-023-03030-8 · Cited by 11 · see citing works
Smith, B. J., Zhao, C., Dubinkina, V. B., Jin, X., Zahavi, L., Shoer, S., Anderson, J. M., Segal, E., & Pollard, K. S. (2025) · Genome Research · doi:10.1101/gr.279543.124 · Cited by 10 · see citing works
Bloom, S. M., Symul, L., Elsherbini, J., Xu, J., Hussain, S., Shih, J. B., Sango, A., Mitchell, C. M., Hemmerling, A., Parks, T., et al. (2026) · Cell Host & Microbe · doi:10.1016/j.chom.2026.03.003 · Cited by 11 · see citing works
SNV-FEAST: microbial source tracking with single nucleotide variants
Briscoe, L., Halperin, E., & Garud, N. R. (2023) · Genome biology · doi:10.1186/s13059-023-02927-8 · Cited by 7 · see citing works
An integrated strain-level analytic pipeline utilizing longitudinal metagenomic data
Zhou, B., Wang, C., Putzel, G., Hu, J., Liu, M., Wu, F., Chen, Y., Pironti, A., & Li, H. (2024) · Microbiology Spectrum · doi:10.1128/spectrum.01431-24 · Cited by 6 · see citing works
Li, Q., Liu, F., Zhong, J., Fang, X., Zhang, X., Xiong, H., Li, G., & Chen, H. (2025) · Frontiers in Microbiology · doi:10.3389/fmicb.2025.1656016 · Cited by 2 · see citing works
Exploring differences in the human gut microbiome between Han Chinese and non-Chinese populations
Wang, J., Zhang, Z., Chen, Y., Zhou, X., Xiang, J., Yang, C., Rodionov, D. A., Osterman, A. L., Qiu, Q., Deng, Y., et al. (2026) · Genome biology · doi:10.1186/s13059-026-03932-3 · Cited by 3 · see citing works
Identifying species-specific k-mers for fast and accurate metagenotyping with Maast and GT-Pro
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · STAR Protocols · doi:10.1016/j.xpro.2022.101964 · Cited by 2 · see citing works
Shalon, N., Relman, D. A., & Yaffe, E. (2022) · Genome Research · doi:10.1101/gr.275894.121 · Cited by 2 · see citing works
EcoFun-MAP: An Ecological Function Oriented Metagenomic Analysis PipelinePreprint
Shi, Z. J., Xiao, N., Ning, D., Tian, R., Zhang, P., Curtis, D., Nostrand, J. D. V., Wu, L., Hazen, T. C., Rocha, A. M., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.05.481366 · Cited by 2 · see citing works
Linkage of nucleotide and functional diversity varies across gut bacteria
Dubinkina, V. B., Smith, B. J., Zhao, C., Pino, C., & Pollard, K. S. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2521012123 · Cited by 1 · see citing works
SNV-FEAST: microbial source tracking with single nucleotide variantsPreprint
Briscoe, L., Halperin, E., & Garud, N. R. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.28.493810 · Cited by 1 · see citing works
Wang, J., Zhang, Z., Chen, Y., Zhou, X., Xiang, J., Yang, C., Rodionov, D. A., Osterman, A. L., Qiu, Q., Deng, Y., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.10.648293 · Cited by 1 · see citing works
Shih, J. B., Bloom, S. M., Xu, J., Mitchell, C. M., Elsherbini, J., & Kwon, D. S. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.08.15.670563 · Cited by 1 · see citing works
Shalon, N., Relman, D. A., & Yaffe, E. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.25.445656
Additional file 10 of Maast: genotyping thousands of microbial strains efficiently
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · Figshare · doi:10.6084/m9.figshare.23930299
Additional file 3 of Maast: genotyping thousands of microbial strains efficiently
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · Figshare · doi:10.6084/m9.figshare.23930278
Additional file 2 of Maast: genotyping thousands of microbial strains efficiently
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · Figshare · doi:10.6084/m9.figshare.23930275
Additional file 9 of Maast: genotyping thousands of microbial strains efficiently
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · Figshare · doi:10.6084/m9.figshare.23930296
Additional file 4 of Maast: genotyping thousands of microbial strains efficiently
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · Figshare · doi:10.6084/m9.figshare.23930281
Additional file 8 of Maast: genotyping thousands of microbial strains efficiently
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · Figshare · doi:10.6084/m9.figshare.23930293
Additional file 6 of Maast: genotyping thousands of microbial strains efficiently
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · Figshare · doi:10.6084/m9.figshare.23930287
Additional file 7 of Maast: genotyping thousands of microbial strains efficiently
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · Figshare · doi:10.6084/m9.figshare.23930290
Additional file 5 of Maast: genotyping thousands of microbial strains efficiently
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · Figshare · doi:10.6084/m9.figshare.23930284
Bloom, S. M., Symul, L., Elsherbini, J., Xu, J., Hussain, S., Shih, J. B., Sango, A., Mitchell, C. M., Hemmerling, A., Parks, T., et al. (2025) · medRxiv · doi:10.1101/2025.08.18.25333897
Wang, D., Yang, X. Y. X., Ren, Z., Hu, B., Zhao, H., Yang, K., Shi, P., Zhang, Z., Feng, Q., Nawenja, C. V., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26704608
Additional file 11 of Maast: genotyping thousands of microbial strains efficiently
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · Figshare · doi:10.6084/m9.figshare.23930302
Additional file 1 of Maast: genotyping thousands of microbial strains efficiently
Shi, Z. J., Nayfach, S., & Pollard, K. S. (2023) · Figshare · doi:10.6084/m9.figshare.23930272
Wang, D., Yang, X. Y. X., Ren, Z., Hu, B., Zhao, H., Yang, K., Shi, P., Zhang, Z., Feng, Q., Nawenja, C. V., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26704602
Wang, D., Yang, X. Y. X., Ren, Z., Hu, B., Zhao, H., Yang, K., Shi, P., Zhang, Z., Feng, Q., Nawenja, C. V., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25583895
Wang, D., Yang, X. Y. X., Ren, Z., Hu, B., Zhao, H., Yang, K., Shi, P., Zhang, Z., Feng, Q., Nawenja, C. V., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25584013
Additional file 1 of SNV-FEAST: microbial source tracking with single nucleotide variants
Briscoe, L., Halperin, E., & Garud, N. R. (2024) · Figshare · doi:10.6084/m9.figshare.26586024
Additional file 2 of SNV-FEAST: microbial source tracking with single nucleotide variants
Briscoe, L., Halperin, E., & Garud, N. R. (2024) · Figshare · doi:10.6084/m9.figshare.26586027
Wang, D., Yang, X. Y. X., Ren, Z., Hu, B., Zhao, H., Yang, K., Shi, P., Zhang, Z., Feng, Q., Nawenja, C. V., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26704605
Genomic Map of Escherichia coli and Single Nucleotide Polymorphism Markers in Colorectal Cancer
Yang, X., Zhong, L., Xu, Y., Yang, X., Jian, C., Caiyun, C., Li, S. H., Zian, Z., Xiaojian, Y., Han, S., et al. (2026) · Microbial Biotechnology · doi:10.1111/1751-7915.70397
Eckhardt, E. R. M., Andreu‐Sánchez, S., Cereghetti, D. M., Tamási, B., Boucard, A.-S., Landsberg, G., Kelly, S., Milanese, A., Klein, B. A., Pagani, E., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-10040780/v1
- Authors
- Shi, Z. J., Dimitrov, B., Zhao, C., Nayfach, S., & Pollard, K. S.
- Affiliations
- Gladstone Institutes (US)
- Chan Zuckerberg Initiative (United States) (US)
- Chan Zuckerberg Biohub San Francisco (US)
- Lawrence Berkeley National Laboratory (US)
- Corresponding author
- Nayfach, Stephen
- Pollard, Katherine S.
- Venue
- Nature Biotechnology
- Published
- 2021-12-23
- Volume
- 40
- Issue
- 4
- Pages
- 507-516
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- OpenAlex
- W4200163820
- Cited by
- 42
- References
- 57
- Citations by year
- 2026: 5 · 2025: 10 · 2024: 10 · 2023: 10 · 2022: 6 · 2021: 1
- FWCI
- 3.12
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Nature Biotechnology (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Science Foundation (DMS-1563159)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Keywords
- human gut microbiome, microbial population structure, prokaryotic genomes
- MeSH terms
- Gastrointestinal Microbiome, Genotype, Humans, Software, Metagenome, Metagenomics, Microbiota
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