Identifying biases and their potential solutions in human microbiome studies

Basic local alignment search tool

Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669 · see citing works

DADA2: High–resolution sample inference from Illumina amplicon data

Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., & Holmes, S. P. (2016) · Nature Methods · doi:10.1038/nmeth.3869 · Cited by 35,698 · see citing works

The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., & Glöckner, F. O. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1219 · Cited by 33,055 · see citing works

Naive Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy

Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007) · Applied and Environmental Microbiology · doi:10.1128/aem.00062-07 · Cited by 19,770 · see citing works

UCHIME improves sensitivity and speed of chimera detection

Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C., & Knight, R. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr381 · Cited by 15,114 · see citing works

VSEARCH: a versatile open source tool for metagenomics

(2016) · doi:10.7717/peerj.2584 · Cited by 10,773 · see citing works

MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph

Li, D., Liu, C.-M., Luo, R., Sadakane, K., & Lam, T. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv033 · Cited by 9,781 · see citing works

Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

Langille, M. G. I., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., Clemente, J. C., Burkepile, D. E., Vega Thurber, R. L., Knight, R., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2676 · Cited by 9,116 · see citing works

Improved metagenomic analysis with Kraken 2

Wood, D. E., Lu, J., & Langmead, B. (2019) · Genome biology · doi:10.1186/s13059-019-1891-0 · Cited by 7,173 · see citing works

Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin

Bokulich, N. A., Kaehler, B. D., Rideout, J. R., Dillon, M. R., Bolyen, E. K., Knight, R. D., Huttley, G. A., & Caporaso, J. G. (2018) · Microbiome · doi:10.1186/s40168-018-0470-z · Cited by 5,873 · see citing works

An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea

McDonald, D. T., Price, M. N., Goodrich, J. K., Nawrocki, E. P., DeSantis, T. Z., Probst, A. J., Andersen, G. L., Knight, R. D., & Hugenholtz, P. (2011) · The ISME Journal · doi:10.1038/ismej.2011.139 · Cited by 5,010 · 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

metaSPAdes: a new versatile metagenomic assembler

Nurk, S., Meleshko, D., Korobeynikov, A., & Pevzner, P. A. (2017) · Genome Research · doi:10.1101/gr.213959.116 · Cited by 4,496 · see citing works

Ribosomal Database Project: data and tools for high throughput rRNA analysis

Cole, J. R., Wang, Q., Fish, J. A., Chai, B., McGarrell, D. M., Sun, Y., Brown, C. T., Porras‐Alfaro, A., Kuske, C. R., & Tiedje, J. M. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1244 · Cited by 4,322 · see citing works

Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data

Davis, N. M., Proctor, D. M., Holmes, S. P., Relman, D. A., & Callahan, B. J. (2018) · Microbiome · doi:10.1186/s40168-018-0605-2 · Cited by 3,493 · see citing works

Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR ampliconsPreprint

Haas, B. J., Gevers, D., Earl, A. M., Feldgarden, M., Ward, D. V., Giannoukos, G., Ciulla, D., Tabbaa, D., Highlander, S. K., Sodergren, E. J., et al. (2011) · Genome Research · doi:10.1101/gr.112730.110 · Cited by 3,480 · see citing works

Reagent and laboratory contamination can critically impact sequence-based microbiome analyses

Salter, S. J., Cox, M. J., Turek, E. M., Calus, S. T., Cookson, W. O., Moffatt, M. F., Turner, P., Parkhill, J., Loman, N. J., & Walker, A. W. (2014) · BMC Biology · doi:10.1186/s12915-014-0087-z · Cited by 3,463 · see citing works

Exact sequence variants should replace operational taxonomic units in marker-gene data analysis

Callahan, B. J., McMurdie, P. J., & Holmes, S. (2017) · The ISME Journal · doi:10.1038/ismej.2017.119 · Cited by 3,253 · see citing works

NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins

Pruitt, K., Tatusova, T., & Maglott, D. (2004) · Nucleic Acids Res. · doi:10.1093/nar/gki025 · Cited by 3,248 · see citing works

Microbiome Datasets Are Compositional: And This Is Not Optional

Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V., & Egozcue, J. J. (2017) · Frontiers in Microbiology · doi:10.3389/fmicb.2017.02224 · Cited by 3,044 · cited 1× · see citing works

Binning metagenomic contigs by coverage and composition

Alneberg, J., Bjarnason, B. S., de Bruijn, I., Schirmer, M., Quick, J., Ijaz, U. Z., Lahti, L., Loman, N. J., Andersson, A. F., & Quince, C. (2014) · Nature Methods · doi:10.1038/nmeth.3103 · Cited by 2,709 · see citing works

Opportunities and challenges in long-read sequencing data analysis

Amarasinghe, S. L., Su, S., Dong, X., Zappia, L., Ritchie, M. E., & Gouil, Q. (2020) · Genome Biology · doi:10.1186/s13059-020-1935-5 · Cited by 2,530 · see citing works

The human tumor microbiome is composed of tumor type–specific intracellular bacteria

Nejman, D., Livyatan, I., Fuks, G., Gavert, N., Zwang, Y., Geller, L. T., Rotter-Maskowitz, A., Weiser, R., Mallel, G., Gigi, E., et al. (2020) · Science · doi:10.1126/science.aay9189 · Cited by 2,464 · see citing works

Role of the gut microbiota in nutrition and health

Valdes, A. M., Walter, J., Segal, E., & Spector, T. D. (2018) · BMJ · doi:10.1136/bmj.k2179 · Cited by 2,375 · cited 1× · see citing works

PacBio Sequencing and its Applications

Rhoads, A., & Au, K. F. (2015) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2015.08.002 · Cited by 2,338 · see citing works

Bracken: estimating species abundance in metagenomics data

(2016) · doi:10.7717/peerj-cs.104 · Cited by 2,333 · see citing works

Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis

Johnson, J. S., Spakowicz, D. J., Hong, B., Petersen, L., Demkowicz, P. C., Chen, L., Leopold, S. R., Hanson, B., Agresta, H. O., Gerstein, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-13036-1 · Cited by 2,286 · see citing works

PCR inhibitors - occurrence, properties and removal

Schrader, C., Schielke, A., Ellerbroek, L., & Johne, R. (2012) · Journal of Applied Microbiology · doi:10.1111/j.1365-2672.2012.05384.x · Cited by 2,129 · see citing works

Best practices for analysing microbiomes

Knight, R., Vrbanac, A., Taylor, B. C., Aksenov, A., Callewaert, C., Debelius, J., Gonzalez, A., Kosciolek, T., McCall, L.-I., McDonald, D., et al. (2018) · Nature Reviews Microbiology · doi:10.1038/s41579-018-0029-9 · Cited by 2,030 · see citing works

Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns

Amir, A., McDonald, D., Navas-Molina, J. A., Kopylova, E., Morton, J. T., Zech Xu, Z., Kightley, E. P., Thompson, L. R., Hyde, E. R., Gonzalez, A., et al. (2017) · mSystems · doi:10.1128/msystems.00191-16 · Cited by 1,881 · see citing works

Microbial seed banks: the ecological and evolutionary implications of dormancy

Lennon, J. T., & Jones, S. E. (2011) · Nature Reviews Microbiology · doi:10.1038/nrmicro2504 · Cited by 1,872 · 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

Extensive Unexplored Human Microbiome Diversity Revealed by Over 150,000 Genomes from Metagenomes Spanning Age, Geography, and Lifestyle

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 complete domain-to-species taxonomy for Bacteria and Archaea

Parks, D. H., Chuvochina, M. S., Chaumeil, P.-A., Rinke, C., Mussig, A. J., & Hugenholtz, P. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0501-8 · Cited by 1,542 · 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

Quantitative microbiome profiling links gut community variation to microbial load

Vandeputte, D., Kathagen, G., D’hoe, K., Vieira-Silva, S., Valles-Colomer, M., Sabino, J., Wang, J., Tito, R. Y., De Commer, L., Darzi, Y., et al. (2017) · Nature · doi:10.1038/nature24460 · Cited by 1,218 · see citing works

The Variability of the 16S rRNA Gene in Bacterial Genomes and Its Consequences for Bacterial Community Analyses

Větrovský, T., & Baldrián, P. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057923 · Cited by 1,201 · see citing works

Stool consistency is strongly associated with gut microbiota richness and composition, enterotypes and bacterial growth rates

Vandeputte, D., Falony, G., Vieira-Silva, S., Tito, R. Y., Joossens, M., & Raes, J. (2016) · Gut · doi:10.1136/gutjnl-2015-309618 · Cited by 1,028 · see citing works

Exploring Microbial Diversity and Taxonomy Using SSU rRNA Hypervariable Tag Sequencing

Huse, S. M., Dethlefsen, L., Huber, J. A., Welch, D. B. M., Relman, D. A., & Sogin, M. L. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000255 · Cited by 993 · see citing works

Towards standards for human fecal sample processing in metagenomic studies

Costea, P. I., Zeller, G., Sunagawa, S., Pelletier, E., Alberti, A., Levenez, F., Tramontano, M., Driessen, M., Hercog, R., Jung, F.-E., et al. (2017) · Nature Biotechnology · doi:10.1038/nbt.3960 · Cited by 893 · see citing works

The Earth Microbiome project: successes and aspirations

Gilbert, J. A., Jansson, J. K., & Knight, R. D. (2014) · BMC Biology · doi:10.1186/s12915-014-0069-1 · Cited by 879 · see citing works

Evaluating rRNA as an indicator of microbial activity in environmental communities: limitations and uses

Blazewicz, S. J., Barnard, R. L., Daly, R. A., & Firestone, M. K. (2013) · The ISME Journal · doi:10.1038/ismej.2013.102 · Cited by 878 · 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

Mucosa-Associated Bacteria in the Human Gastrointestinal Tract Are Uniformly Distributed along the Colon and Differ from the Community Recovered from Feces

Zoetendal, E. G., von Wright, A., Vilpponen-Salmela, T., Ben-Amor, K., Akkermans, A. D. L., & de Vos, W. M. (2002) · Applied and Environmental Microbiology · doi:10.1128/aem.68.7.3401-3407.2002 · Cited by 868 · see citing works

Systematic improvement of amplicon marker gene methods for increased accuracy in microbiome studies

Gohl, D. M., Vangay, P., Garbe, J., Maclean, A., Hauge, A., Becker, A., Gould, T. J., Clayton, J. B., Johnson, T. J., Hunter, R. C., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3601 · Cited by 807 · see citing works

Database resources of the National Center for Biotechnology Information

Sayers, E. W., Barrett, T., Benson, D. A., Bryant, S. H., Canese, K., Chetvernin, V., Church, D. M., DiCuccio, M. N., Edgar, R., Federhen, S., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn741 · Cited by 767 · see citing works

Correcting for 16S rRNA gene copy numbers in microbiome surveys remains an unsolved problem

Louca, S., Doebeli, M., & Parfrey, L. W. (2018) · Microbiome · doi:10.1186/s40168-018-0420-9 · Cited by 755 · 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

Assessing and Improving Methods Used in Operational Taxonomic Unit-Based Approaches for 16S rRNA Gene Sequence Analysis

Schloss, P. D., & Westcott, S. L. (2011) · Applied and Environmental Microbiology · doi:10.1128/aem.02810-10 · Cited by 726 · see citing works

Human placenta has no microbiome but can contain potential pathogens

de Goffau, M. C., Lager, S., Sovio, U., Gaccioli, F., Cook, E., Peacock, S. J., Parkhill, J., Charnock-Jones, D. S., & Smith, G. C. S. (2019) · Nature · doi:10.1038/s41586-019-1451-5 · Cited by 691 · see citing works

GenBank

Benson, D. A., Karsch‐Mizrachi, I., Lipman, D. J., Ostell, J., & Sayers, E. W. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn723 · Cited by 688 · see citing works

Microbiome Helper: a Custom and Streamlined Workflow for Microbiome Research

Comeau, A., Douglas, G. M., & Langille, M. G. I. (2017) · mSystems · doi:10.1128/msystems.00127-16 · Cited by 674 · see citing works

From squiggle to basepair: computational approaches for improving nanopore sequencing read accuracy

Rang, F. J., Kloosterman, W. P., & de Ridder, J. (2018) · Genome biology · doi:10.1186/s13059-018-1462-9 · Cited by 673 · see citing works

NCBI Viral Genomes Resource

Brister, J. R., Ako-adjei, D., Bào, Y., & Blinkova, O. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1207 · Cited by 648 · see citing works

Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture

Yaffe, E., & Tanay, A. (2011) · Nature Genetics · doi:10.1038/ng.947 · Cited by 645 · see citing works

Comparative analysis of fecal DNA extraction methods with phylogenetic microarray: Effective recovery of bacterial and archaeal DNA using mechanical cell lysis

Salonen, A., Nikkilä, J., Jalanka, J., Immonen, O., Rajilić-Stojanović, M. D., Kekkonen, R. A., Palva, A., & de Vos, W. M. (2010) · Journal of Microbiological Methods · doi:10.1016/j.mimet.2010.02.007 · Cited by 592 · see citing works

Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium

The Microbiome Quality Control Project Consortium, Sinha, R., Abu-Ali, G., Vogtmann, E., Fodor, A. A., Ren, B., Amir, A., Schwager, E., Crabtree, J., Ma, S., et al. (2017) · Nature Biotechnology · doi:10.1038/nbt.3981 · Cited by 587 · cited 2× · see citing works

Benchmarking Metagenomics Tools for Taxonomic Classification

Ye, S. H., Siddle, K. J., Park, D. J., & Sabeti, P. C. (2019) · Cell · doi:10.1016/j.cell.2019.07.010 · Cited by 583 · see citing works

The Madness of Microbiome: Attempting To Find Consensus “Best Practice” for 16S Microbiome Studies

Pollock, J., Glendinning, L., Wisedchanwet, T., & Watson, M. (2018) · Applied and Environmental Microbiology · doi:10.1128/aem.02627-17 · Cited by 575 · see citing works

Comparison of placenta samples with contamination controls does not provide evidence for a distinct placenta microbiota

Lauder, A. P., Roche, A. M., Sherrill-Mix, S., Bailey, A., Laughlin, A. L., Bittinger, K., Leite, R., Elovitz, M. A., Parry, S., & Bushman, F. D. (2016) · Microbiome · doi:10.1186/s40168-016-0172-3 · Cited by 539 · see citing works

Human Microbiome in Health and Disease

Pflughoeft, K. J., & Versalovic, J. A. (2011) · Annual Review of Pathology Mechanisms of Disease · doi:10.1146/annurev-pathol-011811-132421 · Cited by 528 · see citing works

Schrödinger’s microbes: Tools for distinguishing the living from the dead in microbial ecosystems

Emerson, J., Adams, R. I., Betancourt‐Román, C. M., Brooks, B., Coil, D. A., Dahlhausen, K. E., Ganz, H. H., Hartmann, E. M., Hsu, T. Y., Justice, N. B., et al. (2017) · Microbiome · doi:10.1186/s40168-017-0285-3 · Cited by 523 · see citing works

Incorporating 16S Gene Copy Number Information Improves Estimates of Microbial Diversity and Abundance

Kembel, S. W., Wu, M., Eisen, J. A., & Green, J. L. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002743 · Cited by 522 · see citing works

Sample storage conditions significantly influence faecal microbiome profiles

Choo, J. M., Leong, L. E. X., & Rogers, G. B. (2015) · Scientific Reports · doi:10.1038/srep16350 · Cited by 506 · see citing works

DNA damage promotes jumping between templates during enzymatic amplification.

Pääbo, S., Irwin, D. M., & Wilson, A. C. (1990) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(19)39621-8 · Cited by 499 · see citing works

Preservation Methods Differ in Fecal Microbiome Stability, Affecting Suitability for Field Studies

Song, S. J., Amir, A., Metcalf, J. L., Amato, K. R., Xu, Z. Z., Humphrey, G. C., & Knight, R. D. (2016) · mSystems · doi:10.1128/msystems.00021-16 · Cited by 484 · see citing works

Effect of storage conditions on the assessment of bacterial community structure in soil and human-associated samples

Lauber, C. L., Zhou, N., Gordon, J. I., Knight, R. D., & Fierer, N. (2010) · FEMS Microbiology Letters · doi:10.1111/j.1574-6968.2010.01965.x · Cited by 463 · see citing works

Contamination and Sensitivity Issues with a Real-Time Universal 16S rRNA PCR

Corless, C., Guiver, M., Borrow, R., Edwards-Jones, V., Kaczmarski, E., & Fox, A. (2000) · Journal of Clinical Microbiology · doi:10.1128/jcm.38.5.1747-1752.2000 · Cited by 453 · see citing works

Microbial abundance, activity and population genomic profiling with mOTUs2

Milanese, A., Mende, D. R., Paoli, L., Salazar, G., Ruscheweyh, H.-J., Cuenca, M., Hingamp, P., Alves, R., Costea, P. I., Coelho, L. P., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08844-4 · Cited by 446 · see citing works

Compositional biases of bacterial genomes and evolutionary implications

Karlin, S., Mrázek, J., & Campbell, A. (1997) · Journal of Bacteriology · doi:10.1128/jb.179.12.3899-3913.1997 · Cited by 442 · see citing works

Consistent and correctable bias in metagenomic sequencing experiments

McLaren, M. R., Willis, A. D., & Callahan, B. J. (2019) · eLife · doi:10.7554/elife.46923 · Cited by 424 · see citing works

Evaluation of PCR-Generated Chimeras, Mutations, and Heteroduplexes with 16S rRNA Gene-Based Cloning

Qiu, X., Wu, L., Huang, H., McDonel, P. E., Palumbo, A. V., Tiedje, J. M., & Zhou, J. Z. (2001) · Applied and Environmental Microbiology · doi:10.1128/aem.67.2.880-887.2001 · Cited by 414 · see citing works

SILVA, RDP, Greengenes, NCBI and OTT — how do these taxonomies compare?

Balvočiūtė, M., & Huson, D. H. (2017) · BMC Genomics · doi:10.1186/s12864-017-3501-4 · Cited by 406 · see citing works

A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling

D’Amore, R., Ijaz, U. Z., Schirmer, M., Kenny, J. G., Gregory, R., Darby, A. C., Shakya, M., Podar, M., Quince, C., & Hall, N. (2016) · BMC Genomics · doi:10.1186/s12864-015-2194-9 · Cited by 405 · see citing works

Whole metagenome profiling reveals skin microbiome-dependent susceptibility to atopic dermatitis flare

Chng, K. R., Tay, A. S. L., Li, C., Ng, A. H. Q., Wang, J., Suri, B. K., Matta, S. A., McGovern, N., Janela, B., Wong, X. F. C. C., et al. (2016) · Nature Microbiology · doi:10.1038/nmicrobiol.2016.106 · Cited by 388 · see citing works

Application of tetranucleotide frequencies for the assignment of genomic fragments

Teeling, H., Meyerdierks, A., Bauer, M., Amann, R., & Glöckner, F. O. (2004) · Environmental Microbiology · doi:10.1111/j.1462-2920.2004.00624.x · Cited by 386 · see citing works

Small-Scale DNA Sample Preparation Method for Field PCR Detection of Microbial Cells and Spores in Soil

Kuske, C. R., Banton, K. L., Adorada, D. L., Stark, P. C., Hill, K. K., & Jackson, P. J. (1998) · Applied and Environmental Microbiology · doi:10.1128/aem.64.7.2463-2472.1998 · Cited by 384 · see citing works

Evaluation of different partial 16S rRNA gene sequence regions for phylogenetic analysis of microbiomes

Kim, M., Morrison, M., & Yu, Z. (2010) · Journal of Microbiological Methods · doi:10.1016/j.mimet.2010.10.020 · Cited by 358 · see citing works

Denoising the Denoisers: an independent evaluation of microbiome sequence error-correction approaches

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

Improving saliva shotgun metagenomics by chemical host DNA depletion

Marotz, C. A., Sanders, J. G., Zúñiga, C., Zaramela, L. S., Knight, R. D., & Zengler, K. (2018) · Microbiome · doi:10.1186/s40168-018-0426-3 · Cited by 348 · see citing works

Comprehensive benchmarking and ensemble approaches for metagenomic classifiers

McIntyre, A. B. R., Ounit, R., Afshinnekoo, E., Prill, R. J., Hénaff, E., Alexander, N., Minot, S. S., Danko, D., Foox, J., Ahsanuddin, S., et al. (2017) · Genome Biology · doi:10.1186/s13059-017-1299-7 · Cited by 342 · see citing works

Cystic fibrosis pathogenesis and the role of biofilms in persistent infection

Costerton, J. W. (2001) · Trends in Microbiology · doi:10.1016/s0966-842x(00)01918-1 · Cited by 329 · see citing works

Absolute quantitation of microbiota abundance in environmental samples

Tkacz, A., Hortala, M., & Poole, P. S. (2018) · Microbiome · doi:10.1186/s40168-018-0491-7 · Cited by 328 · see citing works

Controlling for Contaminants in Low-Biomass 16S rRNA Gene Sequencing Experiments

Karstens, L., Asquith, M. J., Davin, S., Fair, D. A., Gregory, W. T., Wolfe, A. J., Braun, J. G., & McWeeney, S. K. (2019) · mSystems · doi:10.1128/msystems.00290-19 · Cited by 327 · see citing works

Accuracy of taxonomy prediction for 16S rRNA and fungal ITS sequences

Edgar, R. C. (2018) · PeerJ · doi:10.7717/peerj.4652 · Cited by 320 · see citing works

The Effects of Freezing on Faecal Microbiota as Determined Using MiSeq Sequencing and Culture-Based Investigations

Fouhy, F., Deane, J., Rea, M. C., O’Sullivan, Ó., Ross, R. P., O'Callaghan, G. P., Plant, B. J., & Stanton, C. (2015) · PLoS ONE · doi:10.1371/journal.pone.0119355 · Cited by 310 · see citing works

Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding

Krehenwinkel, H., Wolf, M., Lim, J. Y., Rominger, A. J., Simison, W. B., & Gillespie, R. G. (2017) · Scientific Reports · doi:10.1038/s41598-017-17333-x · Cited by 310 · see citing works

Ultrafast and accurate 16S rRNA microbial community analysis using Kraken 2

Lu, J., & Salzberg, S. L. (2020) · Microbiome · doi:10.1186/s40168-020-00900-2 · Cited by 305 · see citing works

Performance Comparison of Illumina and Ion Torrent Next-Generation Sequencing Platforms for 16S rRNA-Based Bacterial Community Profiling

Salipante, S. J., Kawashima, T. I., Rosenthal, C. A., Hoogestraat, D. R., Cummings, L. A., SenGupta, D. J., Harkins, T. T., Cookson, B. T., & Hoffman, N. G. (2014) · Applied and Environmental Microbiology · doi:10.1128/aem.02206-14 · Cited by 302 · see citing works

De novo clustering methods outperform reference-based methods for assigning 16S rRNA gene sequences to operational taxonomic units

Westcott, S. L., & Schloss, P. D. (2015) · PeerJ · doi:10.7717/peerj.1487 · Cited by 296 · see citing works

CopyRighter: a rapid tool for improving the accuracy of microbial community profiles through lineage-specific gene copy number correction

Angly, F. E., Dennis, P. G., Skarshewski, A., Vanwonterghem, I., Hugenholtz, P., & Tyson, G. W. (2014) · Microbiome · doi:10.1186/2049-2618-2-11 · Cited by 293 · see citing works

Comparison of different methods for the isolation and purification of total community DNA from soil

Krsek, M., & Wellington, E. M. H. (1999) · Journal of Microbiological Methods · doi:10.1016/s0167-7012(99)00093-7 · Cited by 283 · see citing works

Isolation of nucleic acids and cultures from fossil ice and permafrost

Willerslev, E., Hansen, A. J., & Poinar, H. N. (2003) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2003.11.010 · Cited by 279 · see citing works

Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms

Costello, M., Fleharty, M., Abreu, J., Farjoun, Y., Ferriera, S., Holmes, L., Granger, B. R., Green, L., Howd, T., Mason, T., et al. (2018) · BMC Genomics · doi:10.1186/s12864-018-4703-0 · Cited by 276 · see citing works

Identifying and Overcoming Threats to Reproducibility, Replicability, Robustness, and Generalizability in Microbiome Research

Schloss, P. D. (2018) · mBio · doi:10.1128/mbio.00525-18 · Cited by 275 · see citing works

Characterization of the total and viable bacterial and fungal communities associated with the International Space Station surfaces

Sielaff, 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

Lack of detection of a human placenta microbiome in samples from preterm and term deliveries

Leiby, J. S., McCormick, K., Sherrill-Mix, S. A., Clarke, E., Kessler, L. R., Taylor, L. J., Hofstaedter, C. E., Roche, A. M., Mattei, L. M., Bittinger, K. L., et al. (2018) · Microbiome · doi:10.1186/s40168-018-0575-4 · Cited by 267 · see citing works

Target Region Selection Is a Critical Determinant of Community Fingerprints Generated by 16S Pyrosequencing

Kumar, P., Brooker, M. R., Dowd, S. E., & Camerlengo, T. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020956 · Cited by 255 · see citing works

Metagenomic Sequencing of an In Vitro-Simulated Microbial Community

Morgan, J. L., Darling, A. E., & Eisen, J. A. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010209 · Cited by 248 · see citing works

Freezing fecal samples prior to DNA extraction affects the Firmicutes to Bacteroidetes ratio determined by downstream quantitative PCR analysis

Bahl, M. I., Bergström, A., & Licht, T. R. (2012) · FEMS Microbiology Letters · doi:10.1111/j.1574-6968.2012.02523.x · Cited by 245 · see citing works

A Molecular Analysis of Fecal and Mucosal Bacterial Communities in Irritable Bowel Syndrome

Codling, C., O’Mahony, L., Shanahan, F., Quigley, E. M. M., & Marchesi, J. R. (2010) · Digestive Diseases and Sciences · doi:10.1007/s10620-009-0934-x · Cited by 243 · see citing works

Comparing and evaluating metagenome assembly tools from a microbiologist's perspective - not only size matters!

Vollmers, J., Wiegand, S., & Kaster, A.-K. (2017) · PLoS ONE · doi:10.1371/journal.pone.0169662 · Cited by 240 · see citing works

Practical considerations for large-scale gut microbiome studies

Vandeputte, D., Tito, R. Y., Vanleeuwen, R., Falony, G., & Raes, J. (2017) · FEMS Microbiology Reviews · doi:10.1093/femsre/fux027 · Cited by 237 · see citing works

Biased 16S rDNA PCR amplification caused by interference from DNA flanking the template region

Hansen, M. C., Tolker‐Nielsen, T., Givskov, M., & Molin, S. (1998) · FEMS Microbiology Ecology · doi:10.1111/j.1574-6941.1998.tb00500.x · Cited by 236 · see citing works

Sequencing 16S rRNA gene fragments using the PacBio SMRT DNA sequencing system.

Schloss, P. D., Jenior, M. L., Koumpouras, C. C., Westcott, S. L., & Highlander, S. K. (2016) · PeerJ · doi:10.7717/peerj.1869 · Cited by 226 · see citing works

Inter-personal diversity and temporal dynamics of dental, tongue, and salivary microbiota in the healthy oral cavity

Hall, M. W., Singh, N., Ng, K. F., Lam, D. K., Goldberg, M. B., Tenenbaum, H. C., Neufeld, J. D., G. Beiko, R., & Senadheera, D. B. (2017) · npj Biofilms and Microbiomes · doi:10.1038/s41522-016-0011-0 · Cited by 226 · see citing works

Accuracy of microbial community diversity estimated by closed- and open-reference OTUs

Edgar, R. C. (2017) · PeerJ · doi:10.7717/peerj.3889 · Cited by 225 · see citing works

Open-Source Sequence Clustering Methods Improve the State Of the Art

Kopylova, E., Navas-Molina, J. A., Mercier, C., Xu, Z. Z., Mahé, F., He, Y., Zhou, H.-W., Rognes, T., Caporaso, J. G., & Knight, R. D. (2016) · mSystems · doi:10.1128/msystems.00003-15 · Cited by 205 · see citing works

DNA extraction method affects microbial community profiles from soils and sediment

Carrigg, C., Rice, O., Kavanagh, S., Collins, G., & O’Flaherty, V. (2007) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-007-1219-y · Cited by 196 · see citing works

Gene annotation bias impedes biomedical research

Haynes, W. A., Tomczak, A., & Khatri, P. (2018) · Scientific Reports · doi:10.1038/s41598-018-19333-x · Cited by 192 · see citing works

Microbial Communities Can Be Described by Metabolic Structure: A General Framework and Application to a Seasonally Variable, Depth-Stratified Microbial Community from the Coastal West Antarctic Peninsula

Bowman, J. S., & Ducklow, H. W. (2015) · PLoS ONE · doi:10.1371/journal.pone.0135868 · Cited by 190 · see citing works

Evaluating variation in human gut microbiota profiles due to DNA extraction method and inter-subject differences

Mackenzie, B. W., Waite, D. W., & Taylor, M. W. (2015) · Frontiers in Microbiology · doi:10.3389/fmicb.2015.00130 · Cited by 189 · see citing works

High proportions of bacteria are culturable across major biomes

Martiny, A. C. (2019) · The ISME Journal · doi:10.1038/s41396-019-0410-3 · Cited by 188 · see citing works

Biased Diversity Metrics Revealed by Bacterial 16S Pyrotags Derived from Different Primer Sets

Cai, L., Ye, L., Tong, A. H. Y., Lok, S., & Zhang, T. (2013) · PLoS ONE · doi:10.1371/journal.pone.0053649 · Cited by 187 · see citing works

Comparison of stool versus rectal swab samples and storage conditions on bacterial community profiles

Bassis, C. M., Moore, N. M., Lolans, K., et al. (2017) · BMC Microbiology · doi:10.1186/s12866-017-0983-9 · Cited by 186 · see citing works

Quantifying and Understanding Well-to-Well Contamination in Microbiome Research

Minich, J. J., Sanders, J. G., Amir, A., Humphrey, G. C., Gilbert, J. A., & Knight, R. D. (2019) · mSystems · doi:10.1128/msystems.00186-19 · Cited by 178 · see citing works

Identification and removal of contaminating microbial DNA from PCR reagents: impact on low-biomass microbiome analyses

Stinson, L. F., Keelan, J. A., & Payne, M. S. (2018) · Letters in Applied Microbiology · doi:10.1111/lam.13091 · Cited by 171 · see citing works

Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity

He, Y., Caporaso, J. G., Jiang, X., Sheng, H.-F., Huse, S. M., Rideout, J. R., Edgar, R. C., Kopylova, E., Walters, W. A., Knight, R. D., et al. (2015) · Microbiome · doi:10.1186/s40168-015-0081-x · Cited by 171 · see citing works

Comparison of methods for fecal microbiome biospecimen collection

Dominianni, C., Wu, J., Hayes, R. B., & Ahn, J. (2014) · BMC Microbiology · doi:10.1186/1471-2180-14-103 · Cited by 170 · see citing works

Assessing Gut Microbial Diversity from Feces and Rectal Mucosa

Durbán, A., Abellan, J. J., Jiménez‐Hernández, N., Ponce, M., Ponce, J. D. C., Sala, T., D’Auria, G., Latorre, A., & Moyá, A. (2010) · Microbial Ecology · doi:10.1007/s00248-010-9738-y · Cited by 165 · see citing works

Quantitative and qualitative assessment of pollen DNA metabarcoding using constructed species mixtures

Bell, K. L., Burgess, K. S., Botsch, J. C., et al. (2018) · Molecular Ecology · doi:10.1111/mec.14840 · Cited by 160 · see citing works

Comparison of Collection Methods for Fecal Samples in Microbiome Studies

Vogtmann, E., Chen, J., Amir, A., Shi, J., Abnet, C. C., Nelson, H., Knight, R. D., Chia, N., & Sinha, R. R. (2016) · American Journal of Epidemiology · doi:10.1093/aje/kww177 · Cited by 159 · see citing works

Assembly complexity of prokaryotic genomes using short reads

Kingsford, C., Schatz, M. C., & Pop, M. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-21 · Cited by 157 · see citing works

Evaluation of strategies for the assembly of diverse bacterial genomes using MinION long-read sequencing

Goldstein, S., Beka, L., Graf, J., & Klassen, J. L. (2019) · BMC Genomics · doi:10.1186/s12864-018-5381-7 · Cited by 154 · see citing works

Performance of Microbiome Sequence Inference Methods in Environments with Varying Biomass

Caruso, V. G., Song, X. B., Asquith, M. J., & Karstens, L. (2019) · mSystems · doi:10.1128/msystems.00163-18 · Cited by 150 · see citing works

Contributions to human breast milk microbiome and enteromammary transfer of Bifidobacterium breve

Kordy, K., Gaufin, T., Mwangi, M., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0219633 · Cited by 148 · see citing works

Effect of preservation method on spider monkey (Ateles geoffroyi) fecal microbiota over 8 weeks

Hale, V. L., Tan, C. L., Knight, R. D., & Amato, K. R. (2015) · Journal of Microbiological Methods · doi:10.1016/j.mimet.2015.03.021 · Cited by 147 · see citing works

Comparison of the sequencing bias of currently available library preparation kits for Illumina sequencing of bacterial genomes and metagenomes

Sato, M. P., Ogura, Y., Nakamura, K., Nishida, R., Gotoh, Y., Hayashi, M., Hisatsune, J., Sugai, M., Itoh, T., & Hayashi, T. (2019) · DNA Research · doi:10.1093/dnares/dsz017 · Cited by 143 · see citing works

The Impact of DNA Polymerase and Number of Rounds of Amplification in PCR on 16S rRNA Gene Sequence Data

Sze, M. A., & Schloss, P. D. (2019) · mSphere · doi:10.1128/msphere.00163-19 · Cited by 139 · see citing works

Studying the gut virome in the metagenomic era: challenges and perspectives

Garmaeva, S., Sinha, T., Kurilshikov, A., Fu, J., Wijmenga, C., & Zhernakova, A. (2019) · BMC Biology · doi:10.1186/s12915-019-0704-y · Cited by 139 · see citing works

DNA extraction for human microbiome studies: the issue of standardization

Greathouse, K. L., Sinha, R., & Vogtmann, E. (2019) · Genome Biology · doi:10.1186/s13059-019-1843-8 · Cited by 138 · see citing works

Inter-niche and inter-individual variation in gut microbial community assessment using stool, rectal swab, and mucosal samples

Jones, R. B., Zhu, X., Moan, E., Murff, H. J., Ness, R. M., Seidner, D. L., Sun, S., Yu, C., Dai, Q., Fodor, A. A., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-22408-4 · Cited by 138 · see citing works

Non-random DNA fragmentation in next-generation sequencing

Poptsova, M. S., Il’icheva, I. A., Nechipurenko, D. Y., Panchenko, L. A., Khodikov, M. V., Oparina, N. Y., Polozov, R. V., Nechipurenko, Y. D., & Grokhovsky, S. L. (2014) · Scientific Reports · doi:10.1038/srep04532 · Cited by 137 · see citing works

Evaluation of different 16S rRNA gene V regions for exploring bacterial diversity in a eutrophic freshwater lake

Zhang, J., Ding, X. L., Guan, R., Zhu, C., Xu, C., Zhu, B., Zhang, H., Xiong, Z., Xue, Y., Tu, J., et al. (2017) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2017.09.228 · Cited by 132 · see citing works

Effects of sampling strategy and DNA extraction on human skin microbiome investigations

Bjerre, R. D., Hugerth, L. W., Boulund, F., Seifert, M., Johansen, J. D., & Engstrand, L. G. (2019) · Scientific Reports · doi:10.1038/s41598-019-53599-z · Cited by 125 · see citing works

Colonic Transit Time Is a Driven Force of the Gut Microbiota Composition and Metabolism: In Vitro Evidence

Tottey, W., Feria-Gervasio, D., Gaci, N., Laillet, B., Pujos, E., Martin, J.-F., Sebedio, J.-L., Sion, B., Jarrige, J.-F., Alric, M., et al. (2017) · Journal of Neurogastroenterology and Motility · doi:10.5056/jnm16042 · Cited by 125 · see citing works

A Comparison of Techniques for Collecting Skin Microbiome Samples: Swabbing Versus Tape-Stripping

Ogai, K., Nagase, S., Mukai, K., Iuchi, T., Mori, Y., Matsue, M., Sugitani, K., Sugama, J., & Okamoto, S. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.02362 · Cited by 120 · see citing works

An Improved DNA Isolation Method for Metagenomic Analysis of the Microbial Flora of the Human Intestine

Morita, H., Kuwahara, T., Ohshima, K., Sasamoto, H., Itoh, K., Hattori, M., Hayashi, T., & Takami, H. (2007) · Microbes and Environments · doi:10.1264/jsme2.22.214 · Cited by 118 · see citing works

A spatial gradient of bacterial diversity in the human oral cavity shaped by salivary flow

Proctor, D. M., Fukuyama, J. A., Loomer, P. M., Armitage, G. C., Lee, S. A., Davis, N. M., Ryder, M. I., Holmes, S. P., & Relman, D. A. (2018) · Nature Communications · doi:10.1038/s41467-018-02900-1 · Cited by 115 · 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

New Approaches to Microbiome-Based Therapies

Wong, A. C., & Levy, M. (2019) · mSystems · doi:10.1128/msystems.00122-19 · Cited by 112 · see citing works

A reanalysis of mouse ENCODE comparative gene expression data

Gilad, Y., & Mizrahi-Man, O. (2015) · F1000Research · doi:10.12688/f1000research.6536.1 · Cited by 100 · see citing works

Correcting for Microbial Blooms in Fecal Samples during Room-Temperature Shipping

Amir, A., McDonald, D. T., Navas-Molina, J. A., Debelius, J. W., Morton, J. T., Hyde, E. R., Robbins‐Pianka, A., & Knight, R. D. (2017) · mSystems · doi:10.1128/msystems.00199-16 · Cited by 98 · see citing works

Elimination of Bacterial DNA from TaqDNA Polymerases by Restriction Endonuclease Digestion

Carroll, N., Adamson, P., & Okhravi, N. (1999) · Journal of Clinical Microbiology · doi:10.1128/jcm.37.10.3402-3404.1999 · Cited by 97 · see citing works

Bacterial community comparisons by taxonomy-supervised analysis independent of sequence alignment and clustering

Sul, W. J., Cole, J. R., Jesus, E. D. C., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1111435108 · Cited by 89 · see citing works

Latitude in sample handling and storage for infant faecal microbiota studies: the elephant in the room?

Shaw, A., Sim, K., Powell, E. A., Cornwell, E., Cramer, T. L. M., McClure, Z. E., Li, M., & Kroll, J. S. (2016) · Microbiome · doi:10.1186/s40168-016-0186-x · Cited by 83 · see citing works

Evaluating metagenomics tools for genome binning with real metagenomic datasets and CAMI datasets

Yue, Y., Huang, H., Qi, Z., Dou, H.-M., Liu, X.-Y., Han, T., Chen, Y.-Q., Song, X.-J., Zhang, Y.-H., & Tu, J. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-03667-3 · Cited by 83 · see citing works

Computational correction of index switching in multiplexed sequencing libraries

Larsson, A. J. M., Stanley, G., Sinha, R., Weissman, I. L., & Sandberg, R. (2018) · Nature Methods · doi:10.1038/nmeth.4666 · Cited by 83 · see citing works

Influence of 16S rRNA variable region on perceived diversity of marine microbial communities of the Northern North Atlantic

Willis, C., Desai, D., & LaRoche, J. (2019) · FEMS Microbiology Letters · doi:10.1093/femsle/fnz152 · Cited by 81 · see citing works

A viability-linked metagenomic analysis of cleanroom environments: eukarya, prokaryotes, and viruses

Weinmaier, T., Probst, A. J., Duc, M. T. L., et al. (2015) · Microbiome · doi:10.1186/s40168-015-0129-y · Cited by 76 · see citing works

Differences in microbial signatures between rectal mucosal biopsies and rectal swabs

Araújo-Pérez, F., McCoy, A. N., Okechukwu, C., Carroll, I. M., Smith, K. M., Jeremiah, K., Sandler, R. S., Asher, G. N., & Keku, T. O. (2012) · Gut Microbes · doi:10.4161/gmic.22157 · Cited by 74 · see citing works

Comparison of the oral microbiome in mouthwash and whole saliva samples

Fan, X., Peters, B. A., Min, D., Ahn, J., & Hayes, R. B. (2018) · PLoS ONE · doi:10.1371/journal.pone.0194729 · Cited by 66 · see citing works

Comparison of 16S rRNA and protein-coding genes as molecular markers for assessing microbial diversity (Bacteria and Archaea) in ecosystems

Roux, S., Enault, F., Bronner, G., et al. (2011) · FEMS Microbiology Ecology · doi:10.1111/j.1574-6941.2011.01190.x · Cited by 65 · see citing works

Comparison of oral microbiome profiles in stimulated and unstimulated saliva, tongue, and mouth-rinsed water

Jo, R., Nishimoto, Y., Umezawa, K., Yama, K., Aita, Y., Ichiba, Y., Murakami, S., Kakizawa, Y., Kumagai, T., Yamada, T., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-52445-6 · Cited by 64 · see citing works

Microbiome Diagnostics

Schlaberg, R. (2019) · Clinical Chemistry · doi:10.1373/clinchem.2019.303248 · Cited by 49 · see citing works

Human faecal collection methods demonstrate a bias in microbiome composition by cell wall structure

Watson, E.-J., Giles, J., Scherer, B. L., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-53183-5 · Cited by 49 · see citing works

Characterization of the bacterial microbiome in first‐pass meconium using propidium monoazide ( PMA ) to exclude nonviable bacterial DNA

Stinson, L. F., Keelan, J. A., & Payne, M. S. (2019) · Letters in Applied Microbiology · doi:10.1111/lam.13119 · Cited by 46 · see citing works

Effects of specimen collection methodologies and storage conditions on the short-term stability of oral microbiome taxonomy

Luo, T., Srinivasan, U., Ramadugu, K., Shedden, K. A., Neiswanger, K., Trumble, E., Li, J. J., McNeil, D. W., Crout, R. J., Weyant, R. J., et al. (2016) · Applied and Environmental Microbiology · doi:10.1128/aem.01132-16 · Cited by 45 · see citing works

Rectal swabs are a reliable proxy for faecal samples in infant gut microbiota research based on 16S-rRNA sequencing

Reyman, M., van Houten, M. A., Arp, K., Sanders, E. A. M., & Bogaert, D. (2019) · Scientific Reports · doi:10.1038/s41598-019-52549-z · Cited by 41 · see citing works

Microbiome of Total Versus Live Bacteria in the Gut of Rex Rabbits

Fu, X., Zeng, B., Wang, P., Wang, L., Wen, B., Li, Y., Liu, H., Bai, S., & Jia, G. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.00733 · Cited by 41 · see citing works

The evolving role of the lung microbiome in pulmonary fibrosis

Lipinski, J. H., Moore, B. B., & O’Dwyer, D. N. (2020) · American Journal of Physiology-Lung Cellular and Molecular Physiology · doi:10.1152/ajplung.00258.2020 · Cited by 38 · see citing works

taxMaps: comprehensive and highly accurate taxonomic classification of short-read data in reasonable timePreprint

Corvelo, A., Clarke, W. E., Robine, N., & Zody, M. C. (2018) · Genome Research · doi:10.1101/gr.225276.117 · Cited by 35 · see citing works

Improved Yield and Accuracy for DNA Extraction in Microbiome Studies with Variation in Microbial Biomass

Davis, A., Kohler, C. M., Alsallaq, R. A., Hayden, R. T., Marón, G. M., & Margolis, E. B. (2019) · BioTechniques · doi:10.2144/btn-2019-0016 · Cited by 33 · see citing works

A simple method for elimination of unspecific amplifications in polymerase chain reaction

Sharma, J. K., Gopalkrishna, V., & Das, B. (1992) · Nucleic Acids Research · doi:10.1093/nar/20.22.6117 · Cited by 28 · see citing works

Rapidly Processed Stool Swabs Approximate Stool Microbiota Profiles

Bokulich, N. A., Maldonado, J., Kang, D., Krajmalnik‐Brown, R., & Caporaso, J. G. (2019) · mSphere · doi:10.1128/msphere.00208-19 · Cited by 28 · see citing works

Microbiota in Exhaled Breath Condensate and the Lung

Glendinning, L., Wright, S. H., Tennant, P. A., et al. (2017) · Applied and Environmental Microbiology · doi:10.1128/aem.00515-17 · Cited by 26 · see citing works

The Role of the Negative Control in Microbiome Analyses

Edmonds, K., & Williams, L. E. (2017) · The FASEB Journal · doi:10.1096/fasebj.31.1_supplement.940.3 · Cited by 18 · see citing works

No bacteria found in healthy placentas

Segata, N. (2019) · Nature · doi:10.1038/d41586-019-02262-8 · Cited by 15 · see citing works

Microbiota–gut–brain axis and its therapeutic applications in neurodegenerative diseases

Loh, J. S., Mak, W. Q., Tan, L. K. S., Ng, C. X., Chan, H. H., Yeow, S. H., Foo, J. B., Ong, Y. S., How, C. W., & Khaw, K. Y. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01743-1 · Cited by 1,193 · see citing works

Quantifying bias introduced by sample collection in relative and absolute microbiome measurements

Maghini, D. G., Dvorak, M., Dahlen, A., Roos, M., Doyle, B., Kuersten, S., & Bhatt, A. S. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-01754-3 · Cited by 116 · see citing works