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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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![Figure 4 Rank abundance curves for control libraries. Rank-abundance curves for defined multi-organism libraries [1] assembled at two different quality thresholds using PANDAseq and naïve assembly followed by clustering with CD-HIT into OTUs of 97% identity.](/paper-figures/c7aa17d75a5648cb9be4d664599fd049/pandaseq-paired-end-assembler-for-illumina-sequences-figure-4.jpg)
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“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
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“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
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“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
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“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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Cites
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 11,490
Needleman, S. B., & Wunsch, C. D. (1970) · Journal of Molecular Biology · doi:10.1016/0022-2836(70)90057-4 · Cited by 11,288
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 10,996
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 9,944
The Ribosomal Database Project: improved alignments and new tools for rRNA analysis
Cole, J. R., Wang, Q., Cardenas, E., Fish, J., Chai, B., Farris, R. J., Kulam-Syed-Mohideen, A. S., McGarrell, D. M., Marsh, T. L., Garrity, G. M., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn879 · Cited by 4,873
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
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
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 800
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 422
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
Research works printed but not linked: 1
- Illumina, Inc: CASAVA Software Version 1.7 User Guide. Illumina, Inc; 2010.
Cited by
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UPARSE: highly accurate OTU sequences from microbial amplicon reads
Edgar, R. C. (2013) · Nature Methods · doi:10.1038/nmeth.2604 · Cited by 16,770
VSEARCH: a versatile open source tool for metagenomics
(2016) · doi:10.7717/peerj.2584 · Cited by 10,773
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 7,246
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
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 4,480
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
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
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
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
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
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 1,315
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 1,259
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
Taberlet, P., Bonin, A., Zinger, L., & Coissac, É. (2018) · doi:10.1093/oso/9780198767220.001.0001 · Cited by 1,146
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 1,070
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
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 1,049
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
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 834
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
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
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 704
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
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
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 596
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 567
Smith, D. P., & Peay, K. (2014) · PLoS ONE · doi:10.1371/journal.pone.0090234 · Cited by 579
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
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 542
Santos‐Medellín, C., Edwards, J. A., Liechty, Z., Nguyen, B., & Sundaresan, V. (2017) · mBio · doi:10.1128/mbio.00764-17 · Cited by 549
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
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
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
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 497
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 506
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
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
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 477
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 467
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
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
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
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
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 392
Sinclair, L., Osman, O. A., Bertilsson, S., & Eiler, A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0116955 · Cited by 385
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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
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 352
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
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 358
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
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
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 359
Parsing ecological signal from noise in next generation amplicon sequencing
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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 325
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 320
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 316
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 309
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 318
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 310
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 302
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
Reintroducing mothur: 10 Years Later
Schloss, P. D. (2019) · Applied and Environmental Microbiology · doi:10.1128/aem.02343-19 · Cited by 298
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
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
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
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 283
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
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 278
Healey, G., Murphy, R., Butts, C., Brough, L., Whelan, K., & Coad, J. (2018) · British Journal Of Nutrition · doi:10.1017/s0007114517003440 · Cited by 267
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 284
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
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 285
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
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
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
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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 267
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
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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
Self-citationCarlson, J. L., Erickson, J. S., Hess, J., Gould, T. J., & Slavin, J. L. (2017) · Nutrients · doi:10.3390/nu9121361 · Cited by 253
Acute dextran sulfate sodium (DSS)‐induced colitis promotes gut microbial dysbiosis in mice
Munyaka, P. M., Rabbi, M. F., Khafipour, E., & Ghia, J. (2016) · Journal of Basic Microbiology · doi:10.1002/jobm.201500726 · Cited by 249
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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., et al. (2016) · Science · doi:10.1126/science.aaf3926 · Cited by 229
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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
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
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Yaari, G., & Kleinstein, S. H. (2015) · Genome Medicine · doi:10.1186/s13073-015-0243-2 · Cited by 224
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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
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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 237
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 224
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
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 231
Abdelfattah, A., Wisniewski, M., Schena, L., & Tack, A. J. M. (2021) · Environmental Microbiology · doi:10.1111/1462-2920.15392 · Cited by 222
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
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 229
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
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
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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
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
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 225
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
Metadata
- 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 › Mathematics › Theoretical Computer Science › 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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