SEPP: SATé-Enabled Phylogenetic Placement
Abstract
We address the problem of Phylogenetic Placement, in which the objective is to insert short molecular sequences (called query sequences) into an existing phylogenetic tree and alignment on full-length sequences for the same gene. Phylogenetic placement has the potential to provide information beyond pure "species identification" (i.e., the association of metagenomic reads to existing species), because it can also give information about the evolutionary relationships between these query sequences and to known species. Approaches for phylogenetic placement have been developed that operate in two steps: first, an alignment is estimated for each query sequence to the alignment of the full-length sequences, and then that alignment is used to find the optimal location in the phylogenetic tree for the query sequence. Recent methods of this type include HMMALIGN+EPA, HMMALIGN+pplacer, and PaPaRa+EPA.We report on a study evaluating phylogenetic placement methods on biological and simulated data. This study shows that these methods have extremely good accuracy and computational tractability under conditions where the input contains a highly accurate alignment and tree for the full-length sequences, and the set of full-length sequences is sufficiently small and not too evolutionarily diverse; however, we also show that under other conditions accuracy declines and the computational requirements for memory and time exceed acceptable limits. We present SEPP, a general "boosting" technique…
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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 state-of-the-art method for building phylogenetic trees from alignments has been shown to be outperformed on gut microbiome data by the placement of sequences into an existing tree with SEPP, which, when sufficient data are available, outperforms de novo phylogeny estimation from alignments.
“The state-of-the-art method for building phylogenetic trees from alignments has been shown to be outperformed on gut microbiome data by the placement of the sequences into an existing tree with SEPP35,36, which, when sufficient data are available, outperforms de novo phylogeny estimation from alignments36.”
From Improving microbial phylogeny with citizen science within a mass-market video game (2025) · cites this paper as [35]
Cites
Still being checked.
Cited by
Sorted by citations
MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability
Katoh, K., & Standley, D. M. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst010 · Cited by 46,209 · see citing works
Manni, M., Berkeley, M. R., Seppey, M., Simão, F. A., & Zdobnov, E. M. (2021) · Molecular Biology and Evolution · doi:10.1093/molbev/msab199 · Cited by 6,187 · see citing works
A communal catalogue reveals Earth's multiscale microbial diversity
Thompson, L. R., Sanders, J. G., McDonald, D., Amir, A., Ladau, J., Locey, K. J., Prill, R. J., Tripathi, A., Gibbons, S. M., Ackermann, G., et al. (2017) · Nature · doi:10.1038/nature24621 · Cited by 2,684 · see citing works
Self-citationBUSCO: Assessing Genomic Data Quality and Beyond
Manni, M., Berkeley, M., Seppey, M., & Zdobnov, E. M. (2021) · Current Protocols · doi:10.1002/cpz1.323 · Cited by 1,303 · see citing works
American Gut: an Open Platform for Citizen-Science Microbiome Research
McDonalda, D., Hyde, E., Debelius, J. W., Morton, J. T., Gonzalez, A., Ackermann, G., Aksenov, A. A., Behsaz, B., Brennan, C., Chen, Y., et al. (2018) · doi:10.1101/277970 · Cited by 878 · see citing works
Asnicar, F., Thomas, A. M., Beghini, F., Mengoni, C., Manara, S., Manghi, P., Zhu, Q., Bolzan, M., Cumbo, F., May, U., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16366-7 · Cited by 869 · see citing works
Self-citationGut microbiota utilize immunoglobulin A for mucosal colonization
Donaldson, G. P., Ladinsky, M. S., Yu, K. B., Sanders, J. G., Yoo, B. B., Chou, W., Conner, M. E., Earl, A. M., Knight, R. D., Björkman, P. J., et al. (2018) · Science · doi:10.1126/science.aaq0926 · Cited by 633 · see citing works
Inflammation-induced IgA+ cells dismantle anti-liver cancer immunity
Shalapour, S., Lin, X.-J., Bastian, I. N., Brain, J., Burt, A. D., Aksenov, A. A., Vrbanac, A. F., Li, W., Perkins, A., Matsutani, T., et al. (2017) · Nature · doi:10.1038/nature24302 · Cited by 589 · see citing works
Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information
Janssen, S., McDonald, D., Gonzalez, A., Navas-Molina, J. A., Jiang, L., Xu, Z. Z., Winker, K., Kado, D. M., Orwoll, E., Manary, M., et al. (2018) · mSystems · doi:10.1128/msystems.00021-18 · Cited by 536 · see citing works
Self-citationComparative Analyses of Vertebrate Gut Microbiomes Reveal Convergence between Birds and Bats
Song, S. J., Sanders, J. G., Delsuc, F., Metcalf, J. L., Amato, K. R., Taylor, M. W., Mazel, F., Lutz, H. L., Winker, K. S., Graves, G. R., et al. (2020) · mBio · doi:10.1128/mbio.02901-19 · Cited by 511 · see citing works
MAFFT: Iterative Refinement and Additional Methods
Katoh, K., & Standley, D. M. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-646-7_8 · Cited by 520 · see citing works
Lücking, R., Aime, M. C., Robbertse, B., Miller, A. N., Ariyawansa, H. A., Aoki, T., Cardinali, G., Crous, P. W., Druzhinina, I. S., Geiser, D. M., et al. (2020) · IMA Fungus · doi:10.1186/s43008-020-00033-z · Cited by 508 · see citing works
Nearing, J. T., Douglas, G. M., Comeau, A., & Langille, M. G. I. (2018) · PeerJ · doi:10.7717/peerj.5364 · Cited by 354 · see citing works
A perspective on 16S rRNA operational taxonomic unit clustering using sequence similarity
Nguyen, N., Warnow, T. J., Pop, M., & White, B. A. (2016) · npj Biofilms and Microbiomes · doi:10.1038/npjbiofilms.2016.4 · Cited by 296 · see citing works
Self-citationSielaff, A. C., Urbaniak, C., Mohan, G. B. M., Stepanov, V. G., Tran, Q. T. T., Wood, J. M., Minich, J. J., McDonald, D. T., Mayer, T., Knight, R. D., et al. (2019) · Microbiome · doi:10.1186/s40168-019-0666-x · Cited by 268 · see citing works
Adding unaligned sequences into an existing alignment using MAFFT and LAST
Katoh, K., & Frith, M. C. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts578 · Cited by 242 · see citing works
Taylor, B. C., Lejzerowicz, F., Poirel, M., Shaffer, J. P., Jiang, L., Aksenov, A., Litwin, N., Humphrey, G., Martino, C., Miller-Montgomery, S., et al. (2020) · mSystems · doi:10.1128/msystems.00901-19 · Cited by 203 · see citing works
Brunt, V. E., Gioscia‐Ryan, R. A., Richey, J. J., Zigler, M. C., Cuevas, L. M., Gonzalez, A., Vázquez‐Baeza, Y., Battson, M. L., Smithson, A. T., Gilley, A. D., et al. (2019) · The Journal of Physiology · doi:10.1113/jp277336 · Cited by 182 · see citing works
GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes
Boyd, J. A., Woodcroft, B. J., & Tyson, G. W. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky174 · Cited by 156 · see citing works
Ultra-large alignments using phylogeny-aware profiles
Nguyen, N., Mirarab, S., Kumar, K., & Warnow, T. J. (2015) · Genome biology · doi:10.1186/s13059-015-0688-z · Cited by 141 · see citing works
Self-citationAnalytical Tools and Databases for Metagenomics in the Next-Generation Sequencing Era
Kim, M., Lee, K.-H., Yoon, S.-W., Kim, B. S., Chun, J., & Yi, H. (2013) · Genomics & Informatics · doi:10.5808/gi.2013.11.3.102 · Cited by 137 · see citing works
Skmer: assembly-free and alignment-free sample identification using genome skims
Sarmashghi, S., Bohmann, K., Gilbert, M. T. P., Bafna, V., & Mirarab, S. (2019) · Genome biology · doi:10.1186/s13059-019-1632-4 · Cited by 134 · see citing works
Self-citationTripathi, A., Melnik, A. V., Xue, J., Poulsen, O., Meehan, M. J., Humphrey, G., Jiang, L., Ackermann, G. L., McDonald, D. T., Zhou, D., et al. (2018) · mSystems · doi:10.1128/msystems.00020-18 · Cited by 134 · see citing works
Ecklu-Mensah, G., Choo-Kang, C., Maseng, M. G., Donato, S., Bovet, P., Viswanathan, B., Bedu-Addo, K., Plange‐Rhule, J., Boateng, P. O., Forrester, T., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-40874-x · Cited by 136 · see citing works
Taxonomic binning of metagenome samples generated by next-generation sequencing technologies
Dröge, J., & McHardy, A. C. (2012) · Briefings in Bioinformatics · doi:10.1093/bib/bbs031 · Cited by 123 · see citing works
Accurate extension of multiple sequence alignments using a phylogeny-aware graph algorithm
Löytynoja, A., Vilella, A. J., & Goldman, N. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts198 · Cited by 123 · see citing works
Assessing the Variation within the Oral Microbiome of Healthy Adults
Nearing, J. T., DeClercq, V., Limbergen, J. V., & Langille, M. G. I. (2020) · mSphere · doi:10.1128/msphere.00451-20 · Cited by 112 · see citing works
Hu, B., Das, P., Lv, X., Shi, M., Aa, J., Wang, K., Duan, L., Gilbert, J. A., Nie, Y., & Wu, X. (2022) · mSystems · doi:10.1128/msystems.00218-22 · Cited by 107 · see citing works
Effects of the microalgae Chlamydomonas on gastrointestinal health
Fields, F. J., Lejzerowicz, F., Schroeder, D., Ngoi, S. M., Tran, M., McDonald, D., Jiang, L., Chang, J. T., Knight, R., & Mayfield, S. (2020) · Journal of Functional Foods · doi:10.1016/j.jff.2019.103738 · Cited by 104 · see citing works
PASTA: Ultra-Large Multiple Sequence Alignment
Mirarab, S., Nguyen, N., & Warnow, T. J. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-05269-4_15 · Cited by 103 · see citing works
Self-citationRepeated sleep disruption in mice leads to persistent shifts in the fecal microbiome and metabolome
Bowers, S. J., Vargas, F., González, A., He, S., Jiang, P., Dorrestein, P. C., Knight, R. D., Wright, K. P., Lowry, C. A., Fleshner, M., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0229001 · Cited by 99 · see citing works
Maricic, I., Marrero, I., Eguchi, A., Nakamura, R., Johnson, C. D., Dasgupta, S., Hernandez, C. D., Nguyen, P. S., Swafford, A. D., Knight, R., et al. (2018) · The Journal of Immunology · doi:10.4049/jimmunol.1800614 · Cited by 92 · see citing works
Mendoza, M. L. Z., Sicheritz‐Pontén, T., & Gilbert, M. T. P. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbv001 · Cited by 87 · see citing works
Cai, L., Zhu, H., Mou, Q., Wong, P. Y., Lan, L., Ng, C. W. K., Pu, L., Cheung, M. K., Wang, D., Wong, E. W. Y., et al. (2024) · npj Biofilms and Microbiomes · doi:10.1038/s41522-024-00511-x · Cited by 89 · see citing works
Amato, K. R., Mallott, E. K., McDonald, D. T., Dominy, N. J., Goldberg, T. L., Lambert, J. E., Swedell, L., Metcalf, J. L., Gomez, A. M., Britton, G. A. O., et al. (2019) · Genome biology · doi:10.1186/s13059-019-1807-z · Cited by 85 · see citing works
Evidence for phylogenetically and catabolically diverse active diazotrophs in deep-sea sediment
Kapili, B. J., Barnett, S. E., Buckley, D. H., & Dekas, A. (2020) · The ISME Journal · doi:10.1038/s41396-019-0584-8 · Cited by 87 · see citing works
Evaluation of the Effect of Storage Methods on Fecal, Saliva, and Skin Microbiome Composition
Marotz, C. A., Cavagnero, K. J., Song, S. J., McDonald, D. T., Wandro, S., Humphrey, G. C., Bryant, M., Ackermann, G. L., Diaz, E., & Knight, R. D. (2021) · mSystems · doi:10.1128/msystems.01329-20 · Cited by 77 · see citing works
A Format for Phylogenetic Placements
Matsen, F. A., IV, Hoffman, N. G., Gallagher, A., & Stamatakis, A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0031009 · Cited by 76 · see citing works
Alderete, T. L., Jones, R. B., Shaffer, J. P., Holzhausen, E. A., Patterson, W. B., Kazemian, E., Chatzi, L., Knight, R. D., Plows, J. F., Berger, P. K., et al. (2021) · Gut Microbes · doi:10.1080/19490976.2021.1961203 · Cited by 66 · see citing works
Lejzerowicz, F., GOODAY, A. J., Angeles, I. B., Cordier, T., Morard, R., Apothéloz‐Perret‐Gentil, L., Lins, L., Menot, L., Brandt, A., Levin, L. A., et al. (2021) · Frontiers in Marine Science · doi:10.3389/fmars.2021.671033 · Cited by 64 · see citing works
Metagenomic Analysis Using Phylogenetic Placement—A Review of the First Decade
Czech, L., Stamatakis, A., Dunthorn, M., & Barbera, P. (2022) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2022.871393 · Cited by 62 · see citing works
Trace Evidence Potential in Postmortem Skin Microbiomes: From Death Scene to Morgue
Kodama, W. A., Xu, Z. Z., Metcalf, J. L., Song, S. J., Harrison, N., Knight, R. D., Carter, D. O., & Happy, C. B. (2018) · Journal of Forensic Sciences · doi:10.1111/1556-4029.13949 · Cited by 62 · see citing works
SCNIC: Sparse correlation network investigation for compositional data
Shaffer, M., Thurimella, K., Sterrett, J. D., & Lozupone, C. (2022) · Molecular Ecology Resources · doi:10.1111/1755-0998.13704 · Cited by 61 · see citing works
Pan, X.-R., Shang-Guan, P.-K., Li, S., Zhang, C.-H., Lou, J.-M., Guo, L., Liu, L., & Lu, Y. (2024) · Environmental Research · doi:10.1016/j.envres.2024.120645 · Cited by 60 · see citing works
Bacterial Communities in Concrete Reflect Its Composite Nature and Change with Weathering
Kiledal, E. A., Keffer, J. L., & Maresca, J. A. (2021) · mSystems · doi:10.1128/msystems.01153-20 · Cited by 56 · see citing works
Beyond the gut: Skin microbiome compositional changes are associated with BMI
Brandwein, M., Katz, I., Katz, A., & Kohen, R. (2019) · Human Microbiome Journal · doi:10.1016/j.humic.2019.100063 · Cited by 57 · see citing works
Golob, J. L., Oskotsky, T., Tang, A., Roldan, A., Chung, V., Ha, C. W. Y., Wong, R. J., Flynn, K. J., Chai, R., Dubin, C., et al. (2023) · Cell Reports Medicine · doi:10.1016/j.xcrm.2023.101350 · Cited by 49 · see citing works
SARS-CoV-2 does not have a strong effect on the nasopharyngeal microbial composition
Braun, T., Halevi, S., Hadar, R., Efroni, G., Saar, E. G., Keller, N., Amir, A., Amit, S., & Haberman, Y. (2021) · Scientific Reports · doi:10.1038/s41598-021-88536-6 · Cited by 48 · see citing works
Armstrong, G., Cantrell, K., Huang, S. W., McDonald, D. T., Haiminen, N., Carrieri, A. P., Zhu, Q., González, A., McGrath, I., Beck, K. L., et al. (2021) · Genome Research · doi:10.1101/gr.275777.121 · Cited by 48 · see citing works
Origin and functional diversification of PAS domain, a ubiquitous intracellular sensor
Xing, J., Gumerov, V. M., & Zhulin, I. B. (2023) · Science Advances · doi:10.1126/sciadv.adi4517 · Cited by 43 · see citing works
Phylogenetics and the Human Microbiome
Matsen, F. A., IV (2014) · Systematic Biology · doi:10.1093/sysbio/syu053 · Cited by 45 · see citing works
Skin inflammation activates intestinal stromal fibroblasts and promotes colitis
Dokoshi, T., Seidman, J. S., Cavagnero, K. J., Li, F., Liggins, M. C., Taylor, B. C., Olvera, J. G., Knight, R. D., Chang, J. T., Salzman, N. H., et al. (2021) · Journal of Clinical Investigation · doi:10.1172/jci147614 · Cited by 43 · see citing works
DEPP: Deep Learning Enables Extending Species Trees using Single Genes
Jiang, Y., Balaban, M., Zhu, Q., & Mirarab, S. (2022) · Systematic Biology · doi:10.1093/sysbio/syac031 · Cited by 40 · see citing works
Self-citationFast and accurate distance‐based phylogenetic placement using divide and conquer
Balaban, M., Jiang, Y., Roush, D., Zhu, Q., & Mirarab, S. (2021) · Molecular Ecology Resources · doi:10.1111/1755-0998.13527 · Cited by 38 · see citing works
Self-citationAbrupt perturbation and delayed recovery of the vaginal ecosystem following childbirth
Costello, E. K., DiGiulio, D. B., Robaczewska, A., Symul, L., Wong, R. J., Shaw, G. M., Stevenson, D. K., Holmes, S., Kwon, D. S., & Relman, D. A. (2023) · Nature Communications · doi:10.1038/s41467-023-39849-9 · Cited by 41 · see citing works
Methods for automatic reference trees and multilevel phylogenetic placement
Czech, L., Barbera, P., & Stamatakis, A. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty767 · Cited by 41 · see citing works
Phylogeny Estimation Given Sequence Length Heterogeneity
Smirnov, V. M., & Warnow, T. J. (2020) · Systematic Biology · doi:10.1093/sysbio/syaa058 · Cited by 37 · see citing works
Self-citationTripathi, A., Xu, Z. Z., Xue, J., Poulsen, O., Gonzalez, A., Humphrey, G., Meehan, M. J., Melnik, A. V., Ackermann, G. L., Zhou, D., et al. (2019) · mSystems · doi:10.1128/msystems.00058-19 · Cited by 35 · see citing works
Turunen, J., Tejesvi, M. V., Paalanne, N., Pokka, T. M.-L., Amatya, S. B., Mishra, S., Kaisanlahti, A., Reunanen, J., & Tapiainen, T. (2023) · Pediatric Research · doi:10.1038/s41390-023-02783-z · Cited by 34 · see citing works
Is there convergence of gut microbes in blood-feeding vertebrates?
Song, S. J., Sanders, J. G., Baldassarre, D. T., Chaves, J. A., Johnson, N. S., Piaggio, A. J., Stuckey, M. J., Nováková, E., Metcalf, J. L., Chomel, B. B., et al. (2019) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2018.0249 · Cited by 35 · see citing works
Nearing, J. T., DeClercq, V., & Langille, M. G. I. (2023) · npj Biofilms and Microbiomes · doi:10.1038/s41522-023-00391-7 · Cited by 30 · see citing works
Edwards, R. J., Dong, C., Park, R., & Tobias, P. A. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.22.489119 · Cited by 30 · see citing works
Adegoke, A., Kumar, D., Budachetri, K., & Karim, S. (2022) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2022.1037387 · Cited by 29 · see citing works
Zhu, H., Yip, H. C., Cheung, M. K., Chan, H. C., Ng, C. W. K., Lau, E. H. L., Yeung, Z. W. C., Wong, E. W. Y., Leung, L. L., Qu, X., et al. (2023) · International Journal of Cancer · doi:10.1002/ijc.34460 · Cited by 33 · see citing works
INSTRAL: Discordance-Aware Phylogenetic Placement Using Quartet Scores
Rabiee, M., & Mirarab, S. (2019) · Systematic Biology · doi:10.1093/sysbio/syz045 · Cited by 27 · see citing works
Self-citationThe microbiome of fly organs and fly-human microbial transfer during decomposition
Deel, H. L., Montoya, S., King, K., Emmons, A. L., Huhn, C., Lynne, A. M., Metcalf, J. L., & BUCHELI, S. R. (2022) · Forensic Science International · doi:10.1016/j.forsciint.2022.111425 · Cited by 26 · see citing works
de Oliveira, N. C., Rodrigues, P. A. P., & Cônsoli, F. L. (2022) · Microbial Ecology · doi:10.1007/s00248-022-02008-6 · Cited by 26 · see citing works
Bowers, S. J., Summa, K. C., Thompson, R. S., González, A., Vargas, F., Olker, C. J., Jiang, P., Lowry, C. A., Dorrestein, P. C., Knight, R. D., et al. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.889211 · Cited by 27 · see citing works
Ticlla, M., Hella, J., Hiza, H. C., Sasamalo, M., Mhimbira, F., Rutaihwa, L. K., Droz, S., Schaller, S., Reither, K., Hilty, M., et al. (2021) · Frontiers in Microbiology · doi:10.3389/fmicb.2021.633396 · Cited by 26 · see citing works
Phenology-dependent root bacteria enhance yield of Brassica napus
Mamet, S. D., Helgason, B. L., Lamb, E. G., McGillivray, A., Stanley, K. G., Robinson, S. J., Aziz, S. U., Vail, S. L., & Siciliano, S. D. (2021) · Soil Biology and Biochemistry · doi:10.1016/j.soilbio.2021.108468 · Cited by 25 · see citing works
Chen, S. H., Rossetto, M., van der Merwe, M. M., Lu‐Irving, P., Yap, J. S., Sauquet, H., Bourke, G., Amos, T. G., Bragg, J. G., & Edwards, R. J. (2022) · Molecular Ecology Resources · doi:10.1111/1755-0998.13574 · Cited by 25 · see citing works
Large-Scale Multiple Sequence Alignment and Tree Estimation Using SATé
Liu, K., & Warnow, T. J. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-646-7_15 · Cited by 25 · see citing works
Self-citationRahman, G., McDonald, D. T., González, A., Vázquez‐Baeza, Y., Jiang, L., Casals‐Pascual, C., Hakim, D., Dilmore, A. H., Nowinski, B., Peddada, S., et al. (2023) · Genes · doi:10.3390/genes14061239 · Cited by 23 · see citing works
HIPPI: highly accurate protein family classification with ensembles of HMMs
Nguyen, N., Nute, M., Mirarab, S., & Warnow, T. J. (2016) · BMC Genomics · doi:10.1186/s12864-016-3097-0 · Cited by 23 · see citing works
Self-citationScheifler, M., Sanchez-Brosseau, S., Magnanou, É., & Desdevises, Y. (2022) · Animal Microbiome · doi:10.1186/s42523-022-00180-1 · Cited by 22 · see citing works
Lyu, Z., Schmidt, R., Martin, R. E., Green, M. T., Kinkade, J. A., Mao, J., Bivens, N. J., Joshi, T., & Rosenfeld, C. S. (2022) · mSystems · doi:10.1128/msystems.00336-22 · Cited by 22 · see citing works
Panah, F. M., Lauridsen, C., Højberg, O., Jensen, H. E., & Nielsen, T. S. (2023) · BMC Microbiology · doi:10.1186/s12866-023-02874-1 · Cited by 22 · see citing works
Anderson, C. J., Boeckaerts, L., Chin, P., Cardás, J. B., Xie, W., Gonçalves, A. C., Blancke, G., Benson, S., Rogatti, S., Simpson, M. S., et al. (2024) · Cell Host & Microbe · doi:10.1016/j.chom.2024.07.026 · Cited by 21 · see citing works
Isolated Grauer's gorilla populations differ in diet and gut microbiome
Michel, A., Minocher, R., Niehoff, P.-P., Li, Y., Nota, K., Gadhvi, M. A., Su, J., Iyer, N., Porter, A. M., Ngobobo, U., et al. (2022) · Molecular Ecology · doi:10.1111/mec.16663 · Cited by 19 · see citing works
Panibe, J. P., Wang, L., Li, J.-Y., Li, M., Lee, Y., Wang, C., Ku, M. S. B., Lu, M. J., & Li, W. (2021) · Genomics · doi:10.1016/j.ygeno.2021.06.006 · Cited by 20 · see citing works
Freeze-drying can replace cold-chains for transport and storage of fecal microbiome samples
Bensch, H. M., Tolf, C., Waldenström, J., Lundin, D., & Zöttl, M. (2022) · PeerJ · doi:10.7717/peerj.13095 · Cited by 20 · see citing works
Large-Scale Multiple Sequence Alignment and Phylogeny Estimation
Warnow, T. J. (2013) · Computational biology · doi:10.1007/978-1-4471-5298-9_6 · Cited by 21 · see citing works
Self-citationTADA: phylogenetic augmentation of microbiome samples enhances phenotype classification
Sayyari, E., Kawas, B., & Mirarab, S. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz394 · Cited by 19 · see citing works
Self-citationSCAMPP: Scaling Alignment-Based Phylogenetic Placement to Large Trees
Wedell, E., Cai, Y., & Warnow, T. (2022) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2022.3170386 · Cited by 19 · see citing works
Self-citationHidalgo-Villeda, F., Million, M., Defoort, C., Vannier, T., Svilar, L., Lagier, M., Wagner, C., Arroyo-Portilla, C., Chasson, L., Luciani, C., et al. (2023) · iScience · doi:10.1016/j.isci.2023.106910 · Cited by 19 · see citing works
High diversity of picornaviruses in rats from different continents revealed by deep sequencing
Hansen, T. A., Mollerup, S., Nguyen, N., White, N. E., Coghlan, M. L., Alquezar‐Planas, D. E., Joshi, T., Jensen, R. H., Fridholm, H., Kjartansdóttir, K. R., et al. (2016) · Emerging Microbes & Infections · doi:10.1038/emi.2016.90 · Cited by 19 · see citing works
Self-citationPPIT: an R package for inferring microbial taxonomy from nifH sequences
Kapili, B. J., & Dekas, A. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab100 · Cited by 15 · see citing works
Vasco, K. A., Nohomovich, B., Singh, P., Venegas-Vargas, C., Mosci, R. E., Rust, S. R., Bartlett, P. C., Norby, B., Grooms, D. L., Zhang, L., et al. (2021) · Microorganisms · doi:10.3390/microorganisms9081737 · Cited by 19 · see citing works
MAGUS+eHMMs: improved multiple sequence alignment accuracy for fragmentary sequences
Shen, C., Zaharias, P., & Warnow, T. J. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab788 · Cited by 18 · see citing works
Self-citationHernández-Becerra, N., Cliffe, L., Xiu, W., Boothman, C., Lloyd, J. R., & Nixon, S. L. (2023) · Environmental Microbiome · doi:10.1186/s40793-023-00465-1 · Cited by 18 · see citing works
Colorado, A. S. B., Lazzaro, A., Neff, C. P., Nusbacher, N. M., Boyd, K., Fiorillo, S. P., Martin, C. G., Siebert, J., Campbell, T., Borok, M. Z., et al. (2024) · Microbiome · doi:10.1186/s40168-023-01718-4 · Cited by 18 · see citing works
Appiah, S. A., Foxx, C. L., Langgartner, D., Palmer, A., Zambrano, C. A., Braumüller, S. T., Schaefer, E. J., Wachter, U. A., Elam, B. L., Radermacher, P., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-85897-w · Cited by 18 · see citing works
Yahfoufi, N., Kadamani, A. K., Aly, S., Sharani, S. A., Liang, J., Butcher, J., Stintzi, A., Matar, C., & Ismail, N. (2022) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2022.09.013 · Cited by 17 · see citing works
Untangling the complex interactions between turtle ants and their microbial partners
Ramalho, M. O., & Moreau, C. S. (2023) · Animal Microbiome · doi:10.1186/s42523-022-00223-7 · Cited by 17 · see citing works
Lascu, I., Locovei, C., Bradu, C., Gheorghiu, C. C., Tănase, A., & Dumitru, A. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms231911230 · Cited by 17 · see citing works
The hidden Markov model and its applications in bioinformatics analysis
Ma, Y., Chen, H., Kang, J., Guo, X., Sun, C., Xu, J., Tao, J., Wei, S., Dong, Y., Tian, H., et al. (2025) · Genes & Diseases · doi:10.1016/j.gendis.2025.101729 · Cited by 18 · see citing works
App-SpaM: phylogenetic placement of short reads without sequence alignment
Blanke, M., & Morgenstern, B. (2021) · Bioinformatics Advances · doi:10.1093/bioadv/vbab027 · Cited by 16 · see citing works
Finlayson-Trick, E. C., Nearing, J. T., Fischer, J. A. J., Ma, Y., Wang, S., Kroeun, H., Goldfarb, D. A., & Karakochuk, C. D. (2023) · Microbiology Spectrum · doi:10.1128/spectrum.05273-22 · Cited by 16 · see citing works
Miller, J. C., Babu, A. K. S., Petersen, C., Wankhade, U. D., Robeson, M. S., Putich, M. N., Mueller, J. E., O'Farrell, A. S., Cho, J. M., Chintapalli, S. V., et al. (2022) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.202200112 · Cited by 17 · see citing works
de Oliveira, A. A., Ramalho, M. O., Moreau, C. S., Campos, A. E. D. C., Harakava, R., & Bueno, O. C. (2022) · Microbiological Research · doi:10.1016/j.micres.2022.127128 · Cited by 15 · see citing works
- Authors
- MIRARAB, S., NGUYEN, N., & WARNOW, T.
- Affiliations
- The University of Texas at Austin (US)
- Venue
- Biocomputing 2012
- Publisher
- WORLD SCIENTIFIC
- Published
- 2011-12
- Pages
- 247-258
- OpenAlex
- W2033900229
- Cited by
- 251
- References
- 0
- Citations by year
- 2026: 13 · 2025: 34 · 2024: 27 · 2023: 37 · 2022: 43 · 2021: 26 · 2020: 14 · 2019: 11 · 2018: 17 · 2017: 3 · 2016: 4 · 2015: 4 · 2014: 4 · 2013: 8 · 2012: 6
- FWCI
- 21.13
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Pacific Symposium on Biocomputing (PSB) (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
- Keywords
- phylogenetic placement, sate, boosting, computational tractability
- MeSH terms
- Algorithms, Bacteria, Phylogeny, RNA, Bacterial, RNA, Ribosomal, 16S, Software, Sequence Alignment, Evolution, Molecular, Computational Biology, Databases, Nucleic Acid, Metagenome, Metagenomics
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
