PANDAseq: paired-end assembler for Illumina sequences
Open accessAbstract
BACKGROUND: Illumina paired-end reads are used to analyse microbial communities by targeting amplicons of the 16S rRNA gene. Publicly available tools are needed to assemble overlapping paired-end reads while correcting mismatches and uncalled bases; many errors could be corrected to obtain higher sequence yields using quality information. RESULTS: PANDAseq assembles paired-end reads rapidly and with the correction of most errors. Uncertain error corrections come from reads with many low-quality bases identified by upstream processing. Benchmarks were done using real error masks on simulated data, a pure source template, and a pooled template of genomic DNA from known organisms. PANDAseq assembled reads more rapidly and with reduced error incorporation compared to alternative methods. CONCLUSIONS: PANDAseq rapidly assembles sequences and scales to billions of paired-end reads. Assembly of control libraries showed a 4-50% increase in the number of assembled sequences over naïve assembly with negligible loss of "good" sequence.
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PANDAseq assumes that all paired-end reads can be merged.
“However, it assumes that all paired-end reads can be merged.”
From PEAR: a fast and accurate Illumina Paired-End reAd mergeR (2014) · cites this paper as Masella et al., 2012
PANDAseq merges fragments by maximizing the probability of true sequence matches, given the observed sequences.
“PANDAseq merges fragments by maximizing the probability of true sequence matches, given the observed sequences.”
From PEAR: a fast and accurate Illumina Paired-End reAd mergeR (2014) · cites this paper as Masella et al., 2012
PANDAseq combines quality scores with sequence matches and thereby improves merging quality.
“It combines quality scores with sequence matches and thereby improves merging quality.”
From PEAR: a fast and accurate Illumina Paired-End reAd mergeR (2014) · cites this paper as Masella et al., 2012
PANDAseq works well with short overlap regions and does not require prior knowledge of the target DNA fragment size.
“In contrast to FLASH, PANDAseq works well with short overlap regions and does not require prior knowledge of the target DNA fragment size.”
From PEAR: a fast and accurate Illumina Paired-End reAd mergeR (2014) · cites this paper as Masella et al., 2012
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Muyzer, G., de Waal, E. C., & Uitterlinden, A. G. (1993) · Applied and Environmental Microbiology · doi:10.1128/aem.59.3.695-700.1993 · Cited by 11,455 · see citing works
Needleman, S. B., & Wunsch, C. D. (1970) · Journal of Molecular Biology · doi:10.1016/0022-2836(70)90057-4 · Cited by 11,288 · see citing works
Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences
Li, W.-Z., & Godzik, A. (2006) · Bioinform. · doi:10.1093/bioinformatics/btl158 · Cited by 10,994 · see citing works
Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Lozupone, C., Turnbaugh, P. J., Fierer, N., & Knight, R. D. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1000080107 · Cited by 9,633 · see citing works
The Ribosomal Database Project: improved alignments and new tools for rRNA analysis
Cole, J., Wang, Q., Cardenas, E., Fish, J., Chai, B., Farris, R. J., Kulam-Syed-Mohideen, A., Mcgarrell, D., Marsh, T., Garrity, G., et al. (2008) · Nucleic Acids Res. · doi:10.1093/nar/gkn879 · Cited by 4,940 · see citing works
Cock, P., Fields, C. J., Goto, N., Heuer, M., & Rice, P. M. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp1137 · Cited by 1,896 · see citing works
The ribosomal database project (RDP-II): introducing myRDP space and quality controlled public data
Cole, J. R., Chai, B., Farris, R. J., Wang, Q., Kulam-Syed-Mohideen, A. S., McGarrell, D. M., Bandela, A. M., Cardenas, E., Garrity, G. M., & Tiedje, J. M. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl889 · Cited by 1,171 · see citing works
Bartram, A. K., Lynch, M. D. J., Stearns, J. C., Moreno‐Hagelsieb, G., & Neufeld, J. D. (2011) · Applied and Environmental Microbiology · doi:10.1128/aem.02772-10 · Cited by 778 · see citing works
Self-citationIllumina-based analysis of microbial community diversity
Degnan, P. H., & Ochman, H. (2011) · The ISME Journal · doi:10.1038/ismej.2011.74 · Cited by 421 · see citing works
Microbiome profiling by Illumina sequencing of combinatorial sequence-tagged PCR products
Gloor, G. B., Hummelen, R., Macklaim, J. M., Dickson, R. J., Fernandes, A. D., MacPhee, R., & Reid, G. (2010) · PLoS ONE · doi:10.1371/journal.pone.0015406 · Cited by 330 · see citing works
BIPES, a cost-effective high-throughput method for assessing microbial diversity
Zhou, H., Li, D., Tam, N. F. Y., Jiang, X., Zhang, H., Sheng, H.-F., Qin, J., Liu, X., & Zou, F. (2010) · The ISME Journal · doi:10.1038/ismej.2010.160 · Cited by 173 · see citing works
Unlocking short read sequencing for metagenomics
Rodrigue, S., Materna, A. C., Timberlake, S. C., Blackburn, M. C., Malmstrom, R. R., Alm, E. J., & Chisholm, S. W. (2010) · PLoS ONE · doi:10.1371/journal.pone.0011840 · Cited by 168 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
UPARSE: highly accurate OTU sequences from microbial amplicon reads
Edgar, R. C. (2013) · Nature Methods · doi:10.1038/nmeth.2604 · Cited by 16,587 · see citing works
VSEARCH: a versatile open source tool for metagenomics
(2016) · doi:10.7717/peerj.2584 · Cited by 10,773 · see citing works
Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K., & Schloss, P. D. (2013) · Applied and Environmental Microbiology · doi:10.1128/aem.01043-13 · Cited by 7,004 · see citing works
PEAR: a fast and accurate Illumina Paired-End reAd mergeR
Zhang, J., Kobert, K., Flouri, T., & Stamatakis, A. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt593 · Cited by 4,497 · 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
Fadrosh, D. W., Ma, B., Gajer, P., Sengamalay, N., Ott, S., Brotman, R. M., & Ravel, J. (2014) · Microbiome · doi:10.1186/2049-2618-2-6 · Cited by 1,698 · see citing works
BBMerge – Accurate paired shotgun read merging via overlap
Bushnell, B., Rood, J., & Singer, E. (2017) · PLoS ONE · doi:10.1371/journal.pone.0185056 · Cited by 1,495 · see citing works
Pushalkar, S., Hundeyin, M., Daley, D., Zambirinis, C. P., Kurz, E., Mishra, A., Mohan, N., Aykut, B., Usyk, M., Torres, L. E., et al. (2018) · Cancer Discovery · doi:10.1158/2159-8290.cd-17-1134 · Cited by 1,400 · see citing works
Thevaranjan, N., Puchta, A., Schulz, C., Naidoo, A., Szamosi, J. C., Verschoor, C. P., Loukov, D., Schenck, L. P., Jury, J., Foley, K. P., et al. (2017) · Cell Host & Microbe · doi:10.1016/j.chom.2017.03.002 · Cited by 1,322 · see citing works
Immunoglobulin A Coating Identifies Colitogenic Bacteria in Inflammatory Bowel Disease
Palm, N. W., de Zoete, M. R., Cullen, T. W., Barry, N. A., Stefanowski, J., Hao, L., Degnan, P. H., Hu, J., Peter, I., Zhang, W., et al. (2014) · Cell · doi:10.1016/j.cell.2014.08.006 · Cited by 1,286 · see citing works
Error filtering, pair assembly and error correction for next-generation sequencing reads
Edgar, R. C., & Flyvbjerg, H. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv401 · Cited by 1,278 · see citing works
Albertsen, M., Hugenholtz, P., Skarshewski, A., Nielsen, K. L., Tyson, G. W., & Nielsen, P. H. (2013) · Nature Biotechnology · doi:10.1038/nbt.2579 · Cited by 1,253 · see citing works
Interaction and signalling between a cosmopolitan phytoplankton and associated bacteria
Amin, S. A., Hmelo, L. R., van Tol, H. M., Durham, B. P., Carlson, L. T., Heal, K. R., Morales, R. L., Berthiaume, C. T., Parker, M. S., Djunaedi, B., et al. (2015) · Nature · doi:10.1038/nature14488 · Cited by 1,125 · see citing works
Taberlet, P., Bonin, A., Zinger, L., & Coissac, É. (2018) · doi:10.1093/oso/9780198767220.001.0001 · Cited by 1,061 · see citing works
Soil pH mediates the balance between stochastic and deterministic assembly of bacteria
Tripathi, B. M., Stegen, J., Kim, M., Dong, K., Adams, J. M., & Lee, Y. K. (2018) · The ISME Journal · doi:10.1038/s41396-018-0082-4 · Cited by 1,049 · see citing works
Gut Microbiota and Extreme Longevity
Biagi, E., Franceschi, C., Rampelli, S., Severgnini, M., Ostan, R., Turroni, S., Consolandi, C., Quercia, S., Scurti, M., Monti, D., et al. (2016) · Current Biology · doi:10.1016/j.cub.2016.04.016 · Cited by 1,025 · see citing works
Swarm: robust and fast clustering method for amplicon-based studies
Mahé, F., Rognes, T., Quince, C., de Vargas, C., & Dunthorn, M. (2014) · PeerJ · doi:10.7717/peerj.593 · Cited by 982 · see citing works
Lagier, J.-C., Khelaifia, S., Alou, M. T., Ndongo, S., Dione, N., Hugon, P., Caputo, A., Cadoret, F., Traore, S. I., Seck, E. H., et al. (2016) · Nature Microbiology · doi:10.1038/nmicrobiol.2016.203 · Cited by 951 · see citing works
RetractedSystematic 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
Pinto-Sanchez, M. I., Hall, G. B., Ghajar, K., Nardelli, A., Bolino, C., Lau, J. T., Martin, F.-P., Cominetti, O., Welsh, C., Rieder, A., et al. (2017) · Gastroenterology · doi:10.1053/j.gastro.2017.05.003 · Cited by 821 · see citing works
Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform
Schirmer, M., Ijaz, U. Z., D'Amore, R., Hall, N., Sloan, W. T., & Quince, C. (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1341 · Cited by 743 · see citing works
High-fat diet alters gut microbiota physiology in mice
Daniel, H., Gholami, A. M., Berry, D., Desmarchelier, C., Hahne, H., Loh, G., Mondot, S., Lepage, P., Rothballer, M., Walker, A., et al. (2013) · The ISME Journal · doi:10.1038/ismej.2013.155 · Cited by 680 · see citing works
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 · see citing works
Zhao, Z., Ning, J., Bao, X.-Q., Shang, M., Ma, J., Li, G., & Zhang, D. (2021) · Microbiome · doi:10.1186/s40168-021-01107-9 · Cited by 616 · see citing works
Tedersoo, L., Anslan, S., Bahram, M., Põlme, S., Riit, T., Liiv, I., Kõljalg, U., Kisand, V., Nilsson, R. H., Hildebrand, F., et al. (2015) · MycoKeys · doi:10.3897/mycokeys.10.4852 · Cited by 586 · see citing works
Deconstructing the Peptide-MHC Specificity of T Cell Recognition
Birnbaum, M. E., Mendoza, J. L., Sethi, D. K., Dong, S., Glanville, J., Dobbins, J., Özkan, E., Davis, M. M., Wucherpfennig, K. W., & García, K. C. (2014) · Cell · doi:10.1016/j.cell.2014.03.047 · Cited by 558 · see citing works
Smith, D. P., & Peay, K. (2014) · PLoS ONE · doi:10.1371/journal.pone.0090234 · Cited by 554 · see citing works
Commonality despite exceptional diversity in the baseline human antibody repertoire
Briney, B., Inderbitzin, A., Joyce, C., & Burton, D. R. (2019) · Nature · doi:10.1038/s41586-019-0879-y · Cited by 544 · see citing works
The activated sludge ecosystem contains a core community of abundant organisms
Saunders, A. M., Albertsen, M., Vollertsen, J., & Nielsen, P. H. (2015) · The ISME Journal · doi:10.1038/ismej.2015.117 · Cited by 543 · see citing works
Santos‐Medellín, C., Edwards, J. A., Liechty, Z., Nguyen, B., & Sundaresan, V. (2017) · mBio · doi:10.1128/mbio.00764-17 · Cited by 527 · see citing works
Microbiota and host determinants of behavioural phenotype in maternally separated mice
De Palma, G., Blennerhassett, P., Lu, J., Deng, Y., Park, A. J., Green, W., Denou, E., Silva, M. A., Santacruz, A., Sanz, Y., et al. (2015) · Nature Communications · doi:10.1038/ncomms8735 · Cited by 517 · see citing works
De Palma, G., Lynch, M. D. J., Lu, J., Dang, V. T., Deng, Y., Jury, J., Umeh, G., Miranda, P. M., Pigrau Pastor, M., Sidani, S., et al. (2017) · Science Translational Medicine · doi:10.1126/scitranslmed.aaf6397 · Cited by 505 · see citing works
Self-citationEdwards, J. A., Santos‐Medellín, C., Liechty, Z., Nguyen, B., Lurie, E., Eason, S., Phillips, G. C., & Sundaresan, V. (2018) · PLoS Biology · doi:10.1371/journal.pbio.2003862 · Cited by 488 · see citing works
Probiotics improve gut microbiota dysbiosis in obese mice fed a high-fat or high-sucrose diet
Kong, C., Gao, R., Yan, X., Huang, L., & Qin, H. (2018) · Nutrition · doi:10.1016/j.nut.2018.10.002 · Cited by 491 · see citing works
Diversity and Activity of Communities Inhabiting Plastic Debris in the North Pacific Gyre
Bryant, J. A., Clemente, T. M., Viviani, D. A., Fong, A. A., Thomas, K. A., Kemp, P. F., Karl, D. M., White, A., & DeLong, E. F. (2016) · mSystems · doi:10.1128/msystems.00024-16 · Cited by 488 · see citing works
Gut microbial metabolism drives transformation of MSH2-deficient colon epithelial cells
Belcheva, A., Irrazabal, T., Robertson, S. J., Streutker, C., Maughan, H., Rubino, S., Moriyama, E. H., Copeland, J. K., Surendra, A., Kumar, S., et al. (2014) · Cell · doi:10.1016/j.cell.2014.04.051 · Cited by 473 · see citing works
Association of host genome with intestinal microbial composition in a large healthy cohort
GEM Project Research Consortium, Turpin, W., Espin-Garcia, O., Xu, W., Silverberg, M. S., Kevans, D., Smith, M. I., Guttman, D. S., Griffiths, A., Panaccione, R., et al. (2016) · Nature Genetics · doi:10.1038/ng.3693 · Cited by 460 · see citing works
Impact of delivery mode-associated gut microbiota dynamics on health in the first year of life
Reyman, M., van Houten, M. A., van Baarle, D., Bosch, A. A. T. M., Man, W. H., Chu, M. L. J. N., Arp, K., Watson, R. L., Sanders, E. A. M., Fuentes, S., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-13014-7 · Cited by 453 · see citing works
Illumina metabarcoding of a soil fungal community
Schmidt, P., Bálint, M., Tzovaras, B. G., Bandow, C., Römbke, J., & Schmitt, I. (2013) · Soil Biology and Biochemistry · doi:10.1016/j.soilbio.2013.05.014 · Cited by 444 · see citing works
Vaginal bacteria modify HIV tenofovir microbicide efficacy in African women
Klatt, N. R., Cheu, R., Birse, K., Zevin, A. S., Perner, M., Noël-Romas, L., Grobler, A., Westmacott, G., Xie, I. Y., Butler, J., et al. (2017) · Science · doi:10.1126/science.aai9383 · Cited by 428 · see citing works
Priming a broadly neutralizing antibody response to HIV-1 using a germline-targeting immunogen
Jardine, J. G., Ota, T., Sok, D., Pauthner, M. G., Kulp, D. W., Kalyuzhniy, O., Skog, P. D., Thinnes, T. C., Bhullar, D., Briney, B. S., et al. (2015) · Science · doi:10.1126/science.aac5894 · Cited by 420 · see citing works
Unraveling gut microbiota in Parkinson's disease and atypical parkinsonism
Barichella, M., Severgnini, M., Cilia, R., Cassani, E., Bolliri, C., Caronni, S., Ferri, V., Cancello, R., Ceccarani, C., Faierman, S., et al. (2019) · Movement Disorders · doi:10.1002/mds.27581 · Cited by 393 · see citing works
Antimicrobial peptide resistance mediates resilience of prominent gut commensals during inflammation
Cullen, T. W., Schofield, W. B., Barry, N. A., Putnam, E. E., Rundell, E. A., Trent, M. S., Degnan, P. H., Booth, C. J., Yu, H., & Goodman, A. L. (2015) · Science · doi:10.1126/science.1260580 · Cited by 395 · see citing works
Pérez‐Jaramillo, J. E., Carrión, V. J., Bosse, M., Ferrão, L. F. V., de Hollander, M., Garcia, A. A. F., Ramírez, C. A., Mendes, R., & Raaijmakers, J. M. (2017) · The ISME Journal · doi:10.1038/ismej.2017.85 · Cited by 391 · see citing works
Sinclair, L., Osman, O. A., Bertilsson, S., & Eiler, A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0116955 · Cited by 364 · see citing works
Bacterial diversity along a 2600 km river continuum
Savio, D., Sinclair, L., Ijaz, U. Z., Párajka, J., Reischer, G. H., Stadler, P., Blaschke, A. P., Blöschl, G., Mach, R. L., Kirschner, A. K. T., et al. (2015) · Environmental Microbiology · doi:10.1111/1462-2920.12886 · Cited by 362 · see citing works
Mesin, L., Schiepers, A., Ersching, J., Barbulescu, A., Cavazzoni, C. B., Angelini, A., Okada, T., Kurosaki, T., & Victora, G. D. (2019) · Cell · doi:10.1016/j.cell.2019.11.032 · Cited by 355 · see citing works
Diversity of vaginal microbiome and metabolome during genital infections
Ceccarani, C., Foschi, C., Parolin, C., D’Antuono, A., Gaspari, V., Consolandi, C., Laghi, L., Camboni, T., Vitali, B., Severgnini, M., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-50410-x · Cited by 351 · see citing works
Ammonia and temperature determine potential clustering in the anaerobic digestion microbiome
Vrieze, J. D., Saunders, A. M., He, Y., Fang, J., Nielsen, P. H., Verstraete, W., & Boon, N. (2015) · Water Research · doi:10.1016/j.watres.2015.02.025 · Cited by 349 · see citing works
A Filtering Method to Generate High Quality Short Reads Using Illumina Paired-End Technology
Eren, A. M., Vineis, J. H., Morrison, H. G., & Sogin, M. L. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066643 · Cited by 350 · see citing works
Falco: high-speed FastQC emulation for quality control of sequencing data
Brandine, G. D. S., & Smith, A. D. (2019) · F1000Research · doi:10.12688/f1000research.21142.2 · Cited by 503 · see citing works
Reyman, M., van Houten, M. A., Watson, R. L., Chu, M. L. J. N., Arp, K., de Waal, W. J., Schiering, I., Plötz, F. B., Willems, R. J. L., van Schaik, W., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28525-z · Cited by 348 · see citing works
Parsing ecological signal from noise in next generation amplicon sequencing
Nguyen, N., Smith, D. P., Peay, K., & Kennedy, P. G. (2014) · New Phytologist · doi:10.1111/nph.12923 · Cited by 320 · see citing works
Cervicovaginal microbiome and natural history of HPV in a longitudinal study
Usyk, M., Zolnik, C. P., Castle, P. E., Porras, C., Herrero, R., Gradíssimo, A., González, P., Safaeian, M., Schiffman, M., Burk, R. D., et al. (2020) · PLoS Pathogens · doi:10.1371/journal.ppat.1008376 · Cited by 316 · see citing works
Sibener, L. V., Fernandes, R. A., Kolawole, E. M., Carbone, C. B., Liu, F., McAffee, D. B., Birnbaum, M. E., Yang, X., Su, L. F., Yu, W., et al. (2018) · Cell · doi:10.1016/j.cell.2018.06.017 · Cited by 312 · see citing works
Davis‐Richardson, A. G., Ardissone, A. N., Dias, R., Simell, V., Leonard, M. T., Kemppainen, K. M., Drew, J. C., Schatz, D., Atkinson, M. A., Kolaczkowski, B., et al. (2014) · Frontiers in Microbiology · doi:10.3389/fmicb.2014.00678 · Cited by 313 · see citing works
Fujio, S., Vasquez, Y., Morales, P., Magne, F., Vera-Wolf, P., Ugalde, J. A., Navarrete, P., & Gotteland, M. (2017) · Frontiers in Microbiology · doi:10.3389/fmicb.2017.01221 · Cited by 304 · see citing works
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
Tavella, T., Rampelli, S., Guidarelli, G., Bazzocchi, A., Gasperini, C., Pujos‐Guillot, E., Comte, B., Barone, M., Biagi, E., Candela, M., et al. (2021) · Gut Microbes · doi:10.1080/19490976.2021.1880221 · Cited by 299 · see citing works
Miranda, P. M., Palma, G. D., Serkis, V., Lu, J., Louis-Auguste, M., McCarville, J. L., Verdu, E. F., Collins, S. M., & Berčík, P. (2018) · Microbiome · doi:10.1186/s40168-018-0433-4 · Cited by 295 · see citing works
Prolonged drought imparts lasting compositional changes to the rice root microbiome
Santos‐Medellín, C., Liechty, Z., Edwards, J. A., Nguyen, B., Huang, B. C., Weimer, B. C., & Sundaresan, V. (2021) · Nature Plants · doi:10.1038/s41477-021-00967-1 · Cited by 280 · see citing works
Reintroducing mothur: 10 Years Later
Schloss, P. D. (2019) · Applied and Environmental Microbiology · doi:10.1128/aem.02343-19 · Cited by 285 · see citing works
Da Silva, H. E., Teterina, A., Comelli, E. M., Taibi, A., Arendt, B. M., Fischer, S. E., Lou, W., & Allard, J. P. (2018) · Scientific Reports · doi:10.1038/s41598-018-19753-9 · Cited by 283 · see citing works
Shaw, K. A., Bertha, M., Hofmekler, T., Chopra, P., Vatanen, T., Srivatsa, A., Prince, J., Kumar, A., Sauer, C. G., Zwick, M. E., et al. (2016) · Genome Medicine · doi:10.1186/s13073-016-0331-y · Cited by 278 · see citing works
Randomized controlled trial for time-restricted eating in healthy volunteers without obesity
Xie, Z., Sun, Y., Ye, Y., Hu, D., Zhang, H., He, Z., Zhao, H., Yang, H., & Mao, Y. (2022) · Nature Communications · doi:10.1038/s41467-022-28662-5 · Cited by 276 · see citing works
A metagenomic study of the gut microbiome in Behcet’s disease
Ye, Z., Zhang, N., Wu, C., Zhang, X., Wang, Q., Huang, X., Du, L., Cao, Q., Tang, J., Zhou, C., et al. (2018) · Microbiome · doi:10.1186/s40168-018-0520-6 · Cited by 272 · see citing works
leeHom: adaptor trimming and merging for Illumina sequencing reads
Renaud, G., Stenzel, U., & Kelso, J. F. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku699 · Cited by 274 · see citing works
Antigen Identification for Orphan T Cell Receptors Expressed on Tumor-Infiltrating Lymphocytes
Gee, M. H., Han, A. S., Lofgren, S., Beausang, J. F., Mendoza, J. L., Birnbaum, M. E., Bethune, M. T., Fischer, S., Yang, X., Gomez, R., et al. (2017) · Cell · doi:10.1016/j.cell.2017.11.043 · Cited by 273 · see citing works
Healey, G., Murphy, R., Butts, C., Brough, L., Whelan, K., & Coad, J. (2018) · British Journal Of Nutrition · doi:10.1017/s0007114517003440 · Cited by 267 · see citing works
The microbiome quality control project: baseline study design and future directions
Sinha, R. R., Abnet, C. C., White, O. R., Knight, R. D., & Huttenhower, C. (2015) · Genome biology · doi:10.1186/s13059-015-0841-8 · Cited by 267 · see citing works
Bauer, P. V., Duca, F. A., Waise, T. M. Z., Rasmussen, B. A., Abraham, M. A., Dranse, H. J., Puri, A., O’Brien, C. A., & Lam, T. K. T. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2017.09.019 · Cited by 265 · see citing works
Dou, S., Gadonna‐Widehem, P., Rome, V., Hamoudi, D., Rhazi, L., Lakhal, L., Larcher, T., Bahi-Jaber, N., Pinon-Quintana, A., Guyonvarch, A., et al. (2017) · PLoS ONE · doi:10.1371/journal.pone.0169851 · Cited by 264 · see citing works
Denou, E., Marcinko, K., Surette, M. G., Steinberg, G. R., & Schertzer, J. D. (2016) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00537.2015 · Cited by 260 · see citing works
Modulation of gut microbiota dysbioses in type 2 diabetic patients by macrobiotic Ma-Pi 2 diet
Candela, M., Biagi, E., Soverini, M., Consolandi, C., Quercia, S., Severgnini, M., Peano, C., Turroni, S., Rampelli, S., Pozzilli, P., et al. (2016) · British Journal Of Nutrition · doi:10.1017/s0007114516001045 · Cited by 260 · see citing works
Bacteria increase arid-land soil surface temperature through the production of sunscreens
Couradeau, E., Karaöz, U., Lim, H. C., da Rocha, U. N., Northen, T. R., Brodie, E., & García‐Pichel, F. (2016) · Nature Communications · doi:10.1038/ncomms10373 · Cited by 260 · see citing works
Tailored Immunogens Direct Affinity Maturation toward HIV Neutralizing Antibodies
Briney, B. S., Sok, D., Jardine, J. G., Kulp, D. W., Skog, P. D., Menis, S., Jacak, R., Kalyuzhniy, O., de Val, N., Sesterhenn, F., et al. (2016) · Cell · doi:10.1016/j.cell.2016.08.005 · Cited by 255 · see citing works
Analysis of plant microbe interactions in the era of next generation sequencing technologies
Knief, C. (2014) · Frontiers in Plant Science · doi:10.3389/fpls.2014.00216 · Cited by 252 · see citing works
Caminero, A., Galipeau, H. J., McCarville, J. L., Johnston, C. W., Bernier, S. P., Russell, A. K., Jury, J., Herran, A. R., Casqueiro, J., Tye-Din, J. A., et al. (2016) · Gastroenterology · doi:10.1053/j.gastro.2016.06.041 · Cited by 250 · see citing works
Evaluating Bias of Illumina-Based Bacterial 16S rRNA Gene Profiles
Kennedy, K. M., Hall, M., Lynch, M. D. J., Moreno‐Hagelsieb, G., & Neufeld, J. D. (2014) · Applied and Environmental Microbiology · doi:10.1128/aem.01451-14 · Cited by 248 · see citing works
Self-citationCarlson, J. L., Erickson, J. S., Hess, J., Gould, T. J., & Slavin, J. L. (2017) · Nutrients · doi:10.3390/nu9121361 · Cited by 245 · see citing works
Acute dextran sulfate sodium (DSS)‐induced colitis promotes gut microbial dysbiosis in mice
Munyaka, P., Rabbi, M. F., Khafipour, E., & Ghia, J. (2016) · Journal of Basic Microbiology · doi:10.1002/jobm.201500726 · Cited by 226 · see citing works
Mx1 reveals innate pathways to antiviral resistance and lethal influenza disease
Pillai, P. S., Molony, R. D., Martinod, K., Dong, H., Pang, I. K., Tal, M. C., Solis, A. G., Bielecki, P., Mohanty, S., Trentalange, M. J., et al. (2016) · Science · doi:10.1126/science.aaf3926 · Cited by 237 · see citing works
Evidence and Role for Bacterial Mucin Degradation in Cystic Fibrosis Airway Disease
Flynn, J. M., Niccum, D. E., Dunitz, J., & Hunter, R. C. (2016) · PLoS Pathogens · doi:10.1371/journal.ppat.1005846 · Cited by 238 · see citing works
Stearns, J. C., Davidson, C. J., McKeon, S., Whelan, F. J., Fontes, M. E., Schryvers, A. B., Bowdish, D. M. E., Kellner, J. D., & Surette, M. G. (2015) · The ISME Journal · doi:10.1038/ismej.2014.250 · Cited by 234 · see citing works
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
Self-citationPractical guidelines for B-cell receptor repertoire sequencing analysis
Yaari, G., & Kleinstein, S. H. (2015) · Genome Medicine · doi:10.1186/s13073-015-0243-2 · Cited by 224 · see citing works
Heavy metal pollution and co-selection for antibiotic resistance: A microbial palaeontology approach
Dickinson, A. W., Power, A. L., Hansen, M. G., Brandt, K. K., Piliposian, G. T., Appleby, P. G., O'Neill, P. A., Jones, R. T., Sierocinski, P., Koskella, B. L., et al. (2019) · Environment International · doi:10.1016/j.envint.2019.105117 · Cited by 226 · see citing works
Glyphosate effects on soil rhizosphere-associated bacterial communities
Newman, M. M., Hoilett, N. O., Lorenz, N., Dick, R. P., Liles, M. R., Ramsier, C., & Kloepper, J. W. (2015) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2015.11.008 · Cited by 225 · see citing works
Stegelmeier, A. A., Müller, K. M., Weese, J. S., & Neufeld, J. D. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1801302115 · Cited by 221 · see citing works
Self-citationJang, L.-G., Choi, G., Kim, S.-W., Kim, B.-Y., Lee, S., & Park, H. (2019) · Journal of the International Society of Sports Nutrition · doi:10.1186/s12970-019-0290-y · Cited by 224 · see citing works
Qiao, S., Liu, C., Sun, L., Wang, T., Dai, H., Wang, K., Li, B., Li, H., Wang, W., Liu, S., et al. (2022) · Nature Metabolism · doi:10.1038/s42255-022-00649-y · Cited by 225 · see citing works
Abdelfattah, A., Wisniewski, M., Schena, L., & Tack, A. J. M. (2021) · Environmental Microbiology · doi:10.1111/1462-2920.15392 · Cited by 222 · see citing works
Synthetic promoter designs enabled by a comprehensive analysis of plant core promoters
Jores, T., Tonnies, J., Wrightsman, T., Buckler, E., Cuperus, J., Fields, S., & Queitsch, C. (2021) · Nature Plants · doi:10.1038/s41477-021-00932-y · Cited by 200 · see citing works
Capturing the diversity of the human gut microbiota through culture-enriched molecular profiling
Lau, J. Y. F., Whelan, F., Herath, I., Lee, C., Collins, S. M., Berčík, P., & Surette, M. G. (2016) · Genome Medicine · doi:10.1186/s13073-016-0327-7 · Cited by 219 · see citing works
Torres, J., Hu, J., Seki, A., Eisele, C., Nair, N., Huang, R., Tarassishin, L., Jharap, B., Cote-Daigneault, J., Mao, Q., et al. (2020) · Gut · doi:10.1136/gutjnl-2018-317855 · Cited by 218 · see citing works
Pérez‐Jaramillo, J. E., de Hollander, M., Ramírez, C. A., Mendes, R., Raaijmakers, J. M., & Carrión, V. J. (2019) · Microbiome · doi:10.1186/s40168-019-0727-1 · Cited by 216 · see citing works
Drought Legacy Effects on the Composition of Soil Fungal and Prokaryote Communities
Meisner, A., Jacquiod, S., Snoek, B. L., ten Hooven, F. C., & van der Putten, W. H. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.00294 · Cited by 214 · see citing works
Rocca, J. D., Simonin, M., Blaszczak, J. R., Ernakovich, J. G., Gibbons, S. M., Midani, F. S., & Washburne, A. D. (2019) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.03272 · Cited by 213 · see citing works
Viral deep sequencing needs an adaptive approach: IRMA, the iterative refinement meta-assembler
Shepard, S. S., Meno, S., Bahl, J., Wilson, M. M., Barnes, J., & Neuhaus, E. B. (2016) · BMC Genomics · doi:10.1186/s12864-016-3030-6 · Cited by 212 · see citing works
Bioinformatic and Statistical Analysis of Adaptive Immune Repertoires
Greiff, V., Miho, E., Menzel, U., & Reddy, S. T. (2015) · Trends in Immunology · doi:10.1016/j.it.2015.09.006 · Cited by 210 · see citing works
- Authors
- Masella, A. P., Bartram, A. K., Truszkowski, J. M., Brown, D. G., & Neufeld, J. D.
- Affiliations
- University of Waterloo (CA)
- Corresponding author
- Neufeld, Josh D
- Venue
- BMC Bioinformatics
- Published
- 2012-02-14
- Volume
- 13
- Issue
- 1
- Pages
- 31-31
- ISSN
- 1471-2105 (ISSN-L)
- PMC
- PMC3471323
- OpenAlex
- W2132548846
- Cited by
- 2,132
- References
- 12
- Citations by year
- 2026: 61 · 2025: 89 · 2024: 90 · 2023: 115 · 2022: 187 · 2021: 254 · 2020: 277 · 2019: 264 · 2018: 251 · 2017: 204 · 2016: 152 · 2015: 108 · 2014: 56 · 2013: 21 · 2012: 3
- FWCI
- 24.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Bioinformatics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Government of Ontario
- Natural Sciences and Engineering Research Council of Canada
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Computer Science › Artificial Intelligence › Algorithms and Data Compression
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Keywords
- 16S rRNA gene, microbial community analysis, error correction, amplicon sequencing, sequencing errors
- MeSH terms
- Bacteria, RNA, Bacterial, RNA, Ribosomal, 16S, Software, Metagenomics
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