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MetaQUAST: evaluation of metagenome assemblies
Open accessAbstract
Summary: During the past years we have witnessed the rapid development of new metagenome assembly methods. Although there are many benchmark utilities designed for single-genome assemblies, there is no well-recognized evaluation and comparison tool for metagenomic-specific analogues. In this article, we present MetaQUAST, a modification of QUAST, the state-of-the-art tool for genome assembly evaluation based on alignment of contigs to a reference. MetaQUAST addresses such metagenome datasets features as (i) unknown species content by detecting and downloading reference sequences, (ii) huge diversity by giving comprehensive reports for multiple genomes and (iii) presence of highly relative species by detecting chimeric contigs. We demonstrate MetaQUAST performance by comparing several leading assemblers on one simulated and two real datasets. Availability and implementation: http://bioinf.spbau.ru/metaquast. Contact: aleksey.gurevich@spbu.ru Supplementary information: Supplementary data are available at Bioinformatics online.
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“Whole genomes of organisms, in addition to strain tracking, can be extracted from the data, allowing for evolutionary analysis of specific organisms associated with a particular disease or environment.79, 80, 81”
From The oral microbiome: Role of key organisms and complex networks in oral health and disease (2021) · cites this paper as [79]
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“1) using MetaQUAST (Mikheenko et al., 2016).”
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“Contig alignment to reference genomes was performed using metaQUAST (Mikheenko et al., 2015).”
MethodNanopore quality score resolution can be reduced with little effect on downstream analysis
Rivara-Espasandín, M., Balestrazzi, L., y Álvarez, G. D., Ochoa, I., Seroussi, G., Smircich, P., Sotelo-Silveira, J. R., & Martín, Á. (2022) · Bioinformatics Advances · doi:10.1093/bioadv/vbac054 · Cited by 8
“5 We evaluated the quality of the final assembly for each run of a polishing pipeline on a data set using MetaQUAST [18] to obtain the number of mismatches per kilobase pairs (kbp) with respect to the combined reference.”
MethodLMAS: evaluating metagenomic short de novo assembly methods through defined communities
Mendes, C. I., Vila-Cerqueira, P., Motro, Y., Moran‐Gilad, J., Carriço, J. A., & Ramirez, M. (2022) · GigaScience · doi:10.1093/gigascience/giac122 · Cited by 9
“MetaQUAST [11], a modification of QUAST, extends the original software by performing assembly evaluation based on aligning contigs to a reference, which can be provided or inferred by the software, and reports, in addition to the standard metrics for single genomes reported by QUAST, the number of interspecies translo…”
MethodGoldberg, T. L., Blevins, E., Leis, E. M., Standish, I., Richard, J. C., Lueder, M. R., Cer, R. Z., & Bishop‐Lilly, K. A. (2023) · Journal of Virology · doi:10.1128/jvi.00196-23 · Cited by 9
Archaea, the tree of life, and cellular evolution in eukaryotes
Xiao, J., Fan, L., Wu, D., Xu, Y., Lai, D., Martin, W. F., Zhu, R., & Zhang, C. (2019) · Science China Earth Sciences · doi:10.1007/s11430-018-9326-1 · Cited by 10
MOSHPIT: accessible, reproducible metagenome data science on the QIIME 2 frameworkPreprint
Ziemski, M., Gehret, L., Simard, A., Dau, S. C., Risch, V., Grabocka, D., Matzoros, C. K., Wood, C., Cabrera, P. M., Hernández-Velázquez, R., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.01.27.635007 · Cited by 9
Ye, L., Zheng, Z., Wang, Y., Hu, Q., Zhong, L., Heng, H., Guo, Z., Li, R., Chan, E. W., & Chen, S. (2024) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2024.171924 · Cited by 8
Banerjee, G., Papri, S. R., & Banerjee, P. (2024) · STAR Protocols · doi:10.1016/j.xpro.2024.103167 · Cited by 8
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Accuracy and Completeness of Long Read Metagenomic Assemblies
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“1.0 (Mikheenko, Saveliev, and Gurevich 2016).”
InfluentialVStrains: De Novo Reconstruction of Viral Strains via Iterative Path Extraction from Assembly Graphs
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“2), (Mikheenko et al., 2015) was used for metagenome assembly evaluation.”
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Choudhari, J. K., Choubey, J., Verma, M. K., Chatterjee, T., & Sahariah, B. P. (2021) · Elsevier eBooks · doi:10.1016/b978-0-323-89775-4.00022-5 · Cited by 8
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Uehara, M., Inoue, T., Kominato, M., Hase, S., Sasaki, E., Toyoda, A., & Sakakibara, Y. (2022) · mSystems · doi:10.1128/msystems.00520-22 · Cited by 8
Metabolically-active obligate aerobes in anoxic (sulfidic) marine sedimentsPreprint
Bhattacharya, S., Roy, C., Mandal, S., Rameez, M. J., Sarkar, J., Fernandes, S., Mapder, T., Alam, M., Roy, R., Mondal, N., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/728287 · Cited by 8
Gauge your phage: Benchmarking of bacteriophage identification tools in metagenomic sequencing dataPreprint
Ho, S. F. S., Wheeler, N. E., Millard, A. D., & van Schaik, W. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.12.438782 · Cited by 8
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CAMI Benchmarking Portal: online evaluation and ranking of metagenomic software
Meyer, F., Robertson, G., Deng, Z.-L., Koslicki, D., Gurevich, A. A., & McHardy, A. C. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf369 · Cited by 8
“…facilitate continuous and accessible benchmarking, we developed the CAMI Benchmarking Portal, which is an easy-to-use web platform integrating the evaluation tools MetaQUAST [ 7 ], AMBER [ 8 ], and OPAL [ 9 ] for assessing metagenome assembly, genome and taxonomic binning, and taxonomic profiling.”
Self-citationGenome-resolved metagenomics from short-read sequencing data in the era of artificial intelligence
Qayyum, H., Ishaq, Z., Ali, A. H., Kayani, M. U. R., & Huang, L. (2025) · Functional & Integrative Genomics · doi:10.1007/s10142-025-01625-x · Cited by 9
“The tool uses a collection of assemblies generated from an initial set of genomes where each contig is described by its specific characteristics and the corresponding misassemblies identified using Meta-QUAST (Mikheenko et al. 2016).”
Naccache, C., Ibrahim, C., Hassen, A., & Khemakhem, M. M. (2025) · PeerJ · doi:10.7717/peerj.19682 · Cited by 7
“2.0 with a metagenomic-adapted pipeline ( Mikheenko, Saveliev & Gurevich, 2016 ).”
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Murphy, R. A., Pizzato, J., Cuthbertson, L., Sabnis, A., Edwards, A. M., Nolan, L. M., Vorup‐Jensen, T., Larrouy-Maumus, G. J., & Davies, J. C. (2024) · npj Antimicrobials and Resistance · doi:10.1038/s44259-024-00022-x · Cited by 7
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Diversity of sulfur cycling halophiles within the Salton Sea, California’s largest lake
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“The quality of the assembled contigs was determined using MetaQuast [25].”
Microorganisms of Two Thermal Pools on Kunashir Island, Russia
Розанов, А. С., Korzhuk, A. V., Шеховцов, С. В., Vasiliev, G. V., & Peltek, S. E. (2021) · Biology · doi:10.3390/biology10090924 · Cited by 7
Sengupta, K., & Pal, S. (2021) · Springer eBooks · doi:10.1007/978-981-16-1350-0_8 · Cited by 7
Generation and application of pseudo–long reads for metagenome assembly
Sim, M., Lee, J., Wy, S., Park, N., Lee, D., Kwon, D., & Kim, J. (2022) · GigaScience · doi:10.1093/gigascience/giac044 · Cited by 7
“The quality of the generated PLRs was then assessed using MetaQUAST [34] in terms of lengths of sequences, the number of sequences, total sequence length, and the number and total length of extremely long sequences (longer than 50 Kbp).”
Chen, Z., & Meng, J. (2022) · Microorganisms · doi:10.3390/microorganisms10122416 · Cited by 7
“2 [27] with the MetaQUAST extension [28] by generating relevant metrics, including the number of contigs, the length of the largest contig (bp), total length (bp), N50, and L50.”
BackgroundDixit, S., Sahoo, K., Gaur, M., Sahoo, R. K., Dey, S., Gupta, V. K., & Subudhi, E. (2023) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2023.113670 · Cited by 7
Selected abstracts of “Bioinformatics: from Algorithms to Applications 2020” conference
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Gut microbial ecology of Xenopus tadpoles across life stagesPreprint
Scalvenzi, T., Clavereau, I., Bourge, M., & Pollet, N. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.05.25.110734 · Cited by 7
Jardim, B. R., Tran‐Nguyen, L. T. T., Gambley, C., Webster, C. G., Kehoe, M. A., Bond, S., Rodoni, B., & Constable, F. E. (2024) · INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY · doi:10.1099/ijsem.0.006502 · Cited by 6
“The remaining phytoplasma-derived contigs were submitted to metaQUAST [16] to estimate the G+C content, genome size and N50 values.”
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Kashchenko, G., Taldaev, A., Сергеевич, А. Л., & Smutin, D. (2025) · Biology · doi:10.3390/biology14010088 · Cited by 6
“After quality control with MetaQUAST [45] (version 5.2.0), IDBA-UD was selected with a k-mer step of 20 and k-mer sizes ranging from 16 to 116, which produced maximal N50.”
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Medina, J. E., Castañeda, S., Camargo, M., García-Corredor, D. J., Muñoz, M., & Ramírez, J. D. (2024) · Veterinary Research Communications · doi:10.1007/s11259-024-10403-2 · Cited by 9
“These assemblies can be assessed for their quality using reference-based or reference-free approaches, such as MetaQUAST and CheckM, respectively (Parks et al. 2015; Mikheenko et al. 2016 ).”
Hidalgo, K., Cueva, L. G., Giachini, A. J., Schneider, M. R., Soriano, A. U., Baessa, M. P. M., Martins, L. F., & Oliveira, V. M. (2025) · Environmental Pollution · doi:10.1016/j.envpol.2025.125685 · Cited by 6
Metagenomic Assembly: Reconstructing Genomes from Metagenomes
Wang, Z., Liang, J., Huang, L., Mengoni, A., & Shu, W. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1099-2_9 · Cited by 6
Colin, L., Yesson, C., & Head, C. E. I. (2021) · Biodiversity Data Journal · doi:10.3897/bdj.9.e72762 · Cited by 6
Zehnpfennig, J. R., Hansel, C. M., Wankel, S. D., Sheik, C. S., Horton, D. J., Lamborg, C. H., & Learman, D. R. (2022) · Frontiers in Marine Science · doi:10.3389/fmars.2022.798877 · Cited by 6
Capturing variation in metagenomic assembly graphs with MetaCortex
Martin, S., Ayling, M., Patrono, L. V., Cáccamo, M., Murcia, P. R., & Leggett, R. M. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad020 · Cited by 6
Ariadne: synthetic long read deconvolution using assembly graphs
Mak, L. E., Meleshko, D., Danko, D., Barakzai, W. N., Maharjan, S., Belchikov, N., & Hajirasouliha, I. (2023) · Genome biology · doi:10.1186/s13059-023-03033-5 · Cited by 6
“As such, we have used similar metaQUAST metrics to evaluate and compare the quality of the assemblies [28].”
MethodProfiling of Active Microorganisms by Stable Isotope Probing—Metagenomics
Kröber, E., & Eyice, Ö. (2019) · Methods in molecular biology · doi:10.1007/978-1-4939-9721-3_12 · Cited by 6
Next-Generation Sequencing: The Enabler and the Way Ahead
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ORFograph: search for novel insecticidal protein genes in genomic and metagenomic assembly graphs
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Bioinformatics for Human Microbiome
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ViQUF: De Novo Viral Quasispecies Reconstruction Using Unitig-Based Flow Networks
Freire, B., Ladra, S., Paramá, J. R., & Salmela, L. (2022) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2022.3190282 · Cited by 5
“We used MetaQUAST [31] for this evaluation.”
InfluentialMATAM: reconstruction of phylogenetic marker genes from short sequencing reads in metagenomesPreprint
Péricard, P., Dufresne, Y., Blanquart, S., & Touzet, H. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/141176 · Cited by 6
“When the sequences present in the sample are actually known (see Sections 4.1 and 4.2), the assembly quality assessment was performed with MetaQuast [18] by aligning the contigs against the original sample sequences, and considering the following metrics: the number of contigs (#contigs), which is…”
MethodInfluentialmetagWGS, a comprehensive workflow to analyze metagenomic data using Illumina or PacBio HiFi readsPreprint
Mainguy, J., Vienne, M., Fourquet, J., Darbot, V., Noirot, C., Castinel, A., Combes, S., Gaspin, C., Denis Milan, A., Donnadieu, C., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.13.612854 · Cited by 6
Achudhan, A. B., & Saleena, L. M. (2024) · World Journal of Microbiology and Biotechnology · doi:10.1007/s11274-024-04174-w · Cited by 5
“1.041( Mikheenko et al. 2016) to evaluate quality metrics and statistics of the de novo assembly.”
InfluentialChase, E. E., Pitot, T. M., Monteil-Bouchard, S., Triplet, S., Przybyla, C., Gobet, A., Desnues, C., & Blanc, G. (2024) · mBio · doi:10.1128/mbio.02803-24 · Cited by 5
Fricker, A. D., Sejane, K., Desai, M., Snyder, M. W., Duran, L., Mackelprang, R., Bode, L., Ross, M. G., & Flores, G. E. (2025) · Nutrients · doi:10.3390/nu17020338 · Cited by 5
“2 [48].”
Thomson, R., Le, C., Wang, L., Batstone, D. J., Zhou, Y., & Oehmen, A. (2025) · Water Research · doi:10.1016/j.watres.2025.123503 · Cited by 5
Li, Y., Polychronopoulou, M., Boonen, I., Fikatas, A., Gryseels, S., Laudisoit, A., de Bellocq, J. G., Vrancken, B., Magiorkinis, G., Lemey, P., et al. (2025) · PLoS ONE · doi:10.1371/journal.pone.0324537 · Cited by 6
“2.0 [30].”
InfluentialSamuelsen, Ø., López-Causapé, C., Aarestrup, F. M., Bortolaia, V., Brouwer, M. S. M., Cantón, R., Egli, A., Grad, Y. H., Hamprecht, A. G., Häußler, S., et al. (2026) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2026.05.012 · Cited by 18
Wickware, C. L., Ellis, A. C., Verma, M. S., & Johnson, T. A. (2025) · Veterinary Microbiology · doi:10.1016/j.vetmic.2025.110372 · Cited by 5
The chemosynthetic biofilm microbiome of deep-sea hydrothermal vents across space and time
Grosche, A., Selci, M., Smedile, F., Giovannelli, D., Borin, S., Bris, N. L., & Vetriani, C. (2025) · Environmental Microbiome · doi:10.1186/s40793-025-00738-x · Cited by 5
Reference-guided assembly of metagenomes with MetaCompass
Luan, T., Cepeda-Espinoza, V. P., Liu, B., Bowen, Z., Ayyangar, U., Almeida, M., Koren, S., Treangen, T. J., Porter, A., & Pop, M. (2025) · Cell Reports Methods · doi:10.1016/j.crmeth.2025.101186 · Cited by 5
“Since MetaCompass builds the assembly with the help of reference genome sequences, the resulting assembly will have an unfair advantage over de novo assemblies when evaluated with MetaQuast.”
Niranjan, V., Setlur, A. S., Skariyachan, S., & Chandrashekar, K. (2023) · Microorganisms for sustainability · doi:10.1007/978-981-19-9570-5_13 · Cited by 5
A dynamic epibiont community associated with the bone-eating polychaete genus Osedax
Goffredi, S. K., Panossian, B., Brzechffa, C., Field, N., King, C., Moggioli, G., Rouse, G. W., Martín-Durán, J. M., & Henry, L. M. (2023) · mBio · doi:10.1128/mbio.03140-22 · Cited by 5
Functional Metagenomics for Identification of Antibiotic Resistance Genes (ARGs)
Cesare, F. D. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1099-2_11 · Cited by 5
Chaouni, B., Azami, A. I., Essayeh, S., Arrafiqui, E. H., Bailal, A., Raoui, S., Amzazi, S., Twaddle, A., Hamouti, C. E., Boukhatem, N., et al. (2022) · Water · doi:10.3390/w14111715 · Cited by 5
Impacts of soybean agriculture on the resistome of the Amazonian soil
Alegria, O. V. C., Quaresma, M. P., Dantas, C. W. D., Lobato, E. M. S. G., Aragão, A. D. O., da Silva, S. P., da Silva, A. C. B., Cruz, A. C. R., Ramos, R. T. J., & Carneiro, A. R. (2022) · Frontiers in Microbiology · doi:10.3389/fmicb.2022.948188 · Cited by 5
“, 2015), with a “meta-large” pattern, and the resulting contigs were analyzed using theMetaquast software (Mikheenko et al., 2016).”
MethodDiversity at single nucleotide to pangenome scales among sulfur cycling bacteria in salt marshes
Castro, S. P., Peredo, E. L., Mason, O. U., Vineis, J. H., Bowen, J. L., Mortazavi, B., Ganesh, A., Ruff, S. E., Paul, B. G., Giblin, A. E., et al. (2023) · Applied and Environmental Microbiology · doi:10.1128/aem.00988-23 · Cited by 5
“” Reads were assembled using MEGAHIT v.1.2.9 (57) and the quality of the four resultant assemblies was evaluated using MetaQUAST v.5.0.2 (58) (Table S2).”
MethodInfluentialMontoya, A. C. V., Mazareli, R. C. D. S., Delforno, T. P., Centurion, V. B., de Oliveira, V. M., Silva, E. L., & Varesche, M. B. A. (2021) · Applied Biochemistry and Biotechnology · doi:10.1007/s12010-021-03725-3 · Cited by 5
Mandal, S., Bhattacharya, S., Roy, C., Rameez, M. J., Sarkar, J., Fernandes, S., Mapder, T., Peketi, A., Mazumdar, A., & Ghosh, W. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/686469 · Cited by 5
“2.x (Li et al., 2015) with the kmers 21, 29, 39, 59, 79, 99, 119 and 141 for a minimum contig-length of 100 bp; each assembly obtained in this way was quality-checked using MetaQUAST (Mikheenko et al., 2016), and >100-bp-long contigs were searched for ORFs/genes encoding >30-amino-acids-long peptides using MetaGeneMar…”
MethodRasmussen, J. A., Villumsen, K. R., Ernst, M., Hansen, M. A., Forberg, T., Gopalakrishnan, S., Gilbert, M. T. P., Bojesen, A. M., Kristiansen, K., & Limborg, M. T. (2021) · Research Square · doi:10.21203/rs.3.rs-916019/v1 · Cited by 5
Altered infective competence of the human gut microbiome in COVID-19Preprint
de Nies, L., Galata, V., Martin‐Gallausiaux, C., Despotović, M., Busi, S. B., Snoeck, C. J., Delacour, L., Budagavi, D. P., Laczny, C. C., Habier, J., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.20.512999 · Cited by 5
Maurice, N., Lemaitre, C., Vicedomini, R., & Frioux, C. (2025) · Bioinformatics · doi:10.1093/bioinformatics/btaf334 · Cited by 4
“MetaQUAST (Mikheenko et al. 2016) performs a reference-based evaluation, either using user-defined references or retrieving references via taxonomic assignment.”
Gene Surfing: An efficient and versatile tool for targeted enzyme mining in metagenomics
Xu, T., Huang, D., Huang, T., Wang, Y., Chen, W., Chen, S., Qian, Y., & Yue, H. (2025) · Synthetic and Systems Biotechnology · doi:10.1016/j.synbio.2025.07.006 · Cited by 4
“2.0) [16], which aligns assemblies against a reference microbial genome database to detect discordant alignments indicative of misassemblies.”
InfluentialArctic Soil C and N Cycling Are Linked With Microbial Adaptations During Drought
Thomsen, T., Schostag, M. D., Priemé, A., & Donhauser, J. (2025) · Global Change Biology · doi:10.1111/gcb.70502 · Cited by 4
“0.2 (Mikheenko et al. 2016).”
InfluentialEvaluation of metagenome binning: advances and challenges
Yazhini, A., Morice, É., Jochheim, A., Lieser, B., & Söding, J. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf617 · Cited by 4
“We evaluated the assembled contigs by MetaQuast [47] and found that coassembled contigs cover 44.99%, 8.4%, and 14.1% fractions of the genomes for the marine, strain-madness,andplant-associated datasets,respectively,while contigs from sample-wise assembly cover 41.1%, 64.7%, and 8.8%.”
InfluentialSagar, K., Priti, K., & Chandra, H. (2026) · Journal of Microbiological Methods · doi:10.1016/j.mimet.2026.107390 · Cited by 4
Metagenomics and bioinformatics in microbial ecology: current status and beyond
De, D., Nayak, T., Das, G., & Dhal, P. K. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-98394-5.00009-2 · Cited by 4
de Farias, B. O., Saggioro, E. M., Montenegro, K. S., Magaldi, M., Santos, H. S. O., Pimenta, R. L., Bianco, K., & Clementino, M. M. (2025) · Chemosphere · doi:10.1016/j.chemosphere.2025.144109 · Cited by 4
Characterization of antibiotic resistance genes in soils from agroecosystems of the Brazilian Amazon
Tavares, T. C. S., Pinto, L. F. D. S., Alegria, O. V. C., Dantas, C. W. D., da Silva, S. P., Cruz, A. C. R., do Rêgo, A. C., Rogez, H. L. G., Ramos, R. T. J., Faturi, C., et al. (2025) · Frontiers in Microbiology · doi:10.3389/fmicb.2025.1508157 · Cited by 4
“Reads were assembled using MEGAHIT 2.4.3 (Li et al., 2015), with specific settings for soil metagenomic data (parameter: meta-large); the resulting contigs were analyzed with the MetaQuast 3.2 (Mikheenko et al., 2016) to assess quality after assembly.”
InfluentialPopov, I. V., Manakhov, A. D., Gorobets, V. E., Diakova, K. B., Lukbanova, E. A., Вячеславович, М. А., Venema, K., Ermakov, A. M., & Popov, I. V. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26135941 · Cited by 4
“Metagenome assembly was performed using metaSPAdes v.4.0.0 [117], and assembly quality was assessed with metaQUAST v.5.2.0 [118].”
InfluentialAci, M. M., AGOSTEO, G. E., Pelle, G., Malacrinò, A., & Schena, L. (2025) · Plant and Soil · doi:10.1007/s11104-025-07623-z · Cited by 4
“Genome assembly quality was assessed using the KBase online platform (Arkin et al. 2018), CheckM v.1.0.18 (Parks et al. 2015) and Quast v.4.4 (Mikheenko et al. 2016).”
InfluentialA practical guide on environmental genomics for prokaryotic systematics
Ernster, N. M., & Rodriguez‐R, L. M. (2025) · Systematic and Applied Microbiology · doi:10.1016/j.syapm.2025.126643 · Cited by 4
Kim, S.-H., Kwon, Y., Park, C., & Kim, H.-R. (2021) · BMC Genomics · doi:10.1186/s12864-021-08122-y · Cited by 4
Deep-Sea Sediments from the Southern Gulf of Mexico Harbor a Wide Diversity of PKS I Genes
Fernández‐López, M. G., Sánchez‐Reyes, A., Barcelos, C., Sidón-Ceseña, K., Leite, R. B., & Lago‐Lestón, A. (2022) · Antibiotics · doi:10.3390/antibiotics11070887 · Cited by 4
Vaitekenas, A., Tai, A. S., Ramsay, J. P., Stick, S. M., Agudelo‐Romero, P., Kicic, A., WAERP, & CF, A. (2022) · Microbiology Resource Announcements · doi:10.1128/mra.00960-22 · Cited by 4
Kumar, A., Robertsen, E. M., Willassen, N. P., Fu, J., & Hjerde, E. (2023) · Genomics & Informatics · doi:10.5808/gi.23072 · Cited by 4
Wattanasombat, S., & Tongjai, S. (2024) · F1000Research · doi:10.12688/f1000research.149577.1 · Cited by 3
“QUAST 63 was utilized to compare contigs from different assemblers, with regular QUAST for single viral isolate datasets and MetaQUAST 63 for multiple isolate inputs.”
Method
Metadata
- Authors
- Mikheenko, A., Saveliev, V., & Gurevich, A.
- Affiliations
- St Petersburg University (RU)
- Corresponding author
- Gurevich, Alexey
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-11-26
- Volume
- 32
- Issue
- 7
- Pages
- 1088-1090
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2175526948
- Cited by
- 711
- References
- 27
- Citations by year
- 2026: 76 · 2025: 100 · 2024: 104 · 2023: 92 · 2022: 78 · 2021: 82 · 2020: 57 · 2019: 44 · 2018: 34 · 2017: 34 · 2016: 9 · 2015: 1
- FWCI
- 11.30
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- Russian Science Foundation (14‐50‐00069, 14-50-)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Environmental Science › Ecology › Environmental DNA in Biodiversity Studies
- Life Sciences › Immunology and Microbiology › Virology › Bacteriophages and microbial interactions
- Keywords
- metagenome assembly, assembly evaluation, QUAST, assembler comparison, contig alignment
- MeSH terms
- Algorithms, Software, Metagenome, Metagenomics, Genomic Structural Variation
About these checks
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