SolexaQA: at-a-glance quality assessment of Illumina second-generation sequencing data
Open accessAbstract
BACKGROUND: Illumina's second-generation sequencing platform is playing an increasingly prominent role in modern DNA and RNA sequencing efforts. However, rapid, simple, standardized and independent measures of run quality are currently lacking, as are tools to process sequences for use in downstream applications based on read-level quality data. RESULTS: We present SolexaQA, a user-friendly software package designed to generate detailed statistics and at-a-glance graphics of sequence data quality both quickly and in an automated fashion. This package contains associated software to trim sequences dynamically using the quality scores of bases within individual reads. CONCLUSION: The SolexaQA package produces standardized outputs within minutes, thus facilitating ready comparison between flow cell lanes and machine runs, as well as providing immediate diagnostic information to guide the manipulation of sequence data for downstream analyses.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
There is an exponential increase in error rates along Illumina reads.
“Furthermore, there is an exponential increase in error rates (ERs) along the reads (Cox et al., 2010).”
From PEAR: a fast and accurate Illumina Paired-End reAd mergeR (2014) · cites this paper as Cox et al., 2010
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,706 · see citing works
Velvet: Algorithms for de novo short read assembly using de Bruijn graphsPreprint
Zerbino, D. R., & Birney, E. (2008) · Genome Research · doi:10.1101/gr.074492.107 · Cited by 9,387 · see citing works
Sequencing technologies – the next generation
Metzker, M. L. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2626 · Cited by 7,066 · 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
Substantial biases in ultra-short read data sets from high-throughput DNA sequencing
Dohm, J. C., Lottaz, C., Borodina, T., & Himmelbauer, H. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn425 · Cited by 1,088 · see citing works
Matrix2png: a utility for visualizing matrix data
Pavlidis, P., & Noble, W. S. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.295 · Cited by 345 · see citing works
Probabilistic base calling of Solexa sequencing data
Rougemont, J., Amzallag, A., Iseli, C., Farinelli, L., Xénarios, I., & Naef, F. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-431 · Cited by 99 · see citing works
PIQA: pipeline for Illumina G1 genome analyzer data quality assessment
Martinez-Alcántara, A., Ballesteros, E., Feng, C., Rojas, M., Koshinsky, H. A., Fofanov, V. Y., Havlak, P., & Fofanov, Y. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp429 · Cited by 50 · see citing works
TileQC: A system for tile-based quality control of Solexa data
Dolan, P. C., & Denver, D. R. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-250 · Cited by 38 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Quality control and preprocessing of metagenomic datasets
Schmieder, R., & Edwards, R. A. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr026 · Cited by 4,989 · 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
NGS QC Toolkit: A Toolkit for Quality Control of Next Generation Sequencing Data
Patel, R. K., & Jain, M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030619 · Cited by 2,921 · see citing works
Chen, Y., Chen, Y., Shi, C., Huang, Z., Zhang, Y., Li, S., Li, Y., Ye, J., Yu, C. H., Li, Z., et al. (2017) · GigaScience · doi:10.1093/gigascience/gix120 · Cited by 2,437 · see citing works
Miya, M. U., Sato, Y., Fukunaga, T., Sado, T., Poulsen, J. Y., Sato, K., Minamoto, T., Yamamoto, S., Yamanaka, H., Araki, H., et al. (2015) · Royal Society Open Science · doi:10.1098/rsos.150088 · Cited by 1,498 · see citing works
Symptomatic atherosclerosis is associated with an altered gut metagenome
Karlsson, F. H., Fåk, F., Nookaew, I., Tremaroli, V., Fagerberg, B., Petranovic, D., Bäckhed, F., & Nielsen, J. (2012) · Nature Communications · doi:10.1038/ncomms2266 · Cited by 1,371 · see citing works
Seasonal cycling in the gut microbiome of the Hadza hunter-gatherers of Tanzania
Smits, S. A., Leach, J., Sonnenburg, E. D., Gonzalez, C. G., Lichtman, J. S., Reid, G., Knight, R., Manjurano, A., Changalucha, J., Elias, J. E., et al. (2017) · Science · doi:10.1126/science.aan4834 · Cited by 886 · see citing works
Minoche, A. E., Dohm, J. C., & Himmelbauer, H. (2011) · Genome biology · doi:10.1186/gb-2011-12-11-r112 · Cited by 620 · see citing works
WebMGA: a customizable web server for fast metagenomic sequence analysis
Wu, S., Zhu, Z., Fu, L., Niu, B., & Li, W. (2011) · BMC Genomics · doi:10.1186/1471-2164-12-444 · Cited by 612 · see citing works
A survey of tools for variant analysis of next-generation genome sequencing data
Pabinger, S., Dander, A., Fischer, M., Snajder, R., Sperk, M., Efremova, M., Krabichler, B., Speicher, M. R., Zschocke, J., & Trajanoski, Z. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbs086 · Cited by 595 · see citing works
Rodriguez‐R, L. M., Gunturu, S., Harvey, W. T., Rossello-Mora, R. A., Tiedje, J. M., Cole, J. R., & Konstantinidis, K. T. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky467 · Cited by 585 · see citing works
Paramsothy, S., Nielsen, S. J., Kamm, M. A., Deshpande, N., Faith, J. J., Clemente, J. C., Paramsothy, R., Walsh, A. J., van den Bogaerde, J., Samuel, D., et al. (2018) · Gastroenterology · doi:10.1053/j.gastro.2018.12.001 · Cited by 516 · see citing works
MG-RAST, a Metagenomics Service for Analysis of Microbial Community Structure and Function
Keegan, K. P., Glass, E. M., & Meyer, F. (2016) · Methods in molecular biology · doi:10.1007/978-1-4939-3369-3_13 · Cited by 494 · see citing works
An Extensive Evaluation of Read Trimming Effects on Illumina NGS Data Analysis
Fabbro, C. D., Scalabrin, S., Morgante, M., & Giorgi, F. M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0085024 · Cited by 478 · see citing works
M e D u S a : a multi-draft based scaffolder
Bosi, E., Donati, B., Galardini, M., Brunetti, S., Sagot, M., Lió, P., Crescenzi, P., Fani, R., & Fondi, M. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv171 · Cited by 429 · see citing works
Oulas, A., Pavloudi, C., Polymenakou, P., Pavlopoulos, G. A., Papanikolaou, N., Kotoulas, G., Arvanitidis, C., & Iliopoulos, L. (2015) · Bioinformatics and Biology Insights · doi:10.4137/bbi.s12462 · Cited by 423 · see citing works
Filippis, F. D., Pasolli, E., Tett, A., Tarallo, S., Naccarati, A., Angelis, M. D., Neviani, E., Cocolin, L., Gobbetti, M., Segata, N., et al. (2019) · Cell Host & Microbe · doi:10.1016/j.chom.2019.01.004 · Cited by 399 · see citing works
DNA methylome analysis using short bisulfite sequencing data
Krueger, F., Kreck, B., Franke, A., & Andrews, S. (2012) · Nature Methods · doi:10.1038/nmeth.1828 · Cited by 366 · see citing works
Dynamic Transcriptome Landscape of Maize Embryo and Endosperm Development
Chen, J., Zeng, B., Zhang, M., Xie, S., Wang, G., Hauck, A. L., & Lai, J. (2014) · PLANT PHYSIOLOGY · doi:10.1104/pp.114.240689 · Cited by 367 · see citing works
AfterQC: automatic filtering, trimming, error removing and quality control for fastq data
Chen, S., Huang, T., Zhou, Y., Han, Y., Xu, M., & Gu, J. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1469-3 · Cited by 354 · see citing works
Stimulation of Piezo1 by mechanical signals promotes bone anabolism
Li, X., Han, L., Nookaew, I., Mannen, E. M., Silva, M. J., Almeida, M., & Xiong, J. (2019) · eLife · doi:10.7554/elife.49631 · Cited by 361 · see citing works
Bergkemper, F., Schöler, A., Engel, M., Lang, F., Krüger, J., Schloter, M., & Schulz, S. (2015) · Environmental Microbiology · doi:10.1111/1462-2920.13188 · Cited by 352 · see citing works
Programmable RNA editing with compact CRISPR–Cas13 systems from uncultivated microbes
Xu, C., Zhou, Y., Xiao, Q., He, B., Geng, G., Wang, Z., Cao, B., Dong, X., Bai, W., Wang, Y., et al. (2021) · Nature Methods · doi:10.1038/s41592-021-01124-4 · Cited by 351 · see citing works
Nookaew, I., Papini, M., Pornputtapong, N., Scalcinati, G., Fagerberg, L., Uhlén, M., & Nielsen, J. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks804 · Cited by 309 · see citing works
Assessment of Metagenomic Assembly Using Simulated Next Generation Sequencing Data
Mende, D. R., Waller, A. S., Sunagawa, S., Järvelin, A. I., Chan, M. M., Arumugam, M., Raes, J., & Peer Bork, B. (2012) · PLoS ONE · doi:10.1371/journal.pone.0031386 · Cited by 305 · see citing works
Sato, Y., Miya, M. U., Fukunaga, T., Sado, T., & Iwasaki, W. (2018) · Molecular Biology and Evolution · doi:10.1093/molbev/msy074 · Cited by 296 · see citing works
Rapid evaluation and quality control of next generation sequencing data with FaQCs
Lo, C., & Chain, P. (2014) · BMC Bioinformatics · doi:10.1186/s12859-014-0366-2 · Cited by 284 · see citing works
Nonpareil 3: Fast Estimation of Metagenomic Coverage and Sequence Diversity
Rodriguez‐R, L. M., Gunturu, S., Tiedje, J. M., Cole, J. R., & Konstantinidis, K. T. (2018) · mSystems · doi:10.1128/msystems.00039-18 · Cited by 267 · see citing works
Nonpareil: a redundancy-based approach to assess the level of coverage in metagenomic datasets
Rodriguez‐R, L. M., & Konstantinidis, K. T. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt584 · Cited by 257 · see citing works
A Histone Acetyltransferase Regulates Active DNA Demethylation in Arabidopsis
Qian, W., Miki, D., Zhang, H., Liu, Y., Zhang, X., Tang, K., Kan, Y., La, H., Li, X., Li, S., et al. (2012) · Science · doi:10.1126/science.1219416 · Cited by 253 · see citing works
TMK1-mediated auxin signalling regulates differential growth of the apical hook
Cao, M., Chen, R., Li, P., Yu, Y., Zheng, R., Ge, D., Zheng, W., Wang, X., Gu, Y., Gelová, Z., et al. (2019) · Nature · doi:10.1038/s41586-019-1069-7 · Cited by 253 · see citing works
Pandit, R. J., Hinsu, A., Patel, N. V., KORINGA, P. G., Jakhesara, S. J., Thakkar, J. R., Shah, T. M., Limon, G., Psifidi, A., Guitián, J., et al. (2018) · Microbiome · doi:10.1186/s40168-018-0501-9 · Cited by 243 · see citing works
Criscuolo, A., & Brisse, S. (2013) · Genomics · doi:10.1016/j.ygeno.2013.07.011 · Cited by 243 · see citing works
LR_Gapcloser: a tiling path-based gap closer that uses long reads to complete genome assembly
Xu, G.-C., Xu, T., Zhu, R., Zhang, Y., Li, S.-Q., Wang, H.-W., & Li, J.-T. (2018) · GigaScience · doi:10.1093/gigascience/giy157 · Cited by 240 · see citing works
Widely Used Benzalkonium Chloride Disinfectants Can Promote Antibiotic Resistance
Kim, M., Weigand, M. R., Oh, S., Hatt, J. K., Krishnan, R., Tezel, U., Pavlostathis, S. G., & Konstantinidis, K. T. (2018) · Applied and Environmental Microbiology · doi:10.1128/aem.01201-18 · Cited by 239 · see citing works
ConDeTri - A Content Dependent Read Trimmer for Illumina Data
Smeds, L., & Künstner, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0026314 · Cited by 226 · see citing works
Distinct gut microbiome patterns associate with consensus molecular subtypes of colorectal cancer
Purcell, R. V., Visnovska, M., Biggs, P. J., Schmeier, S., & Frizelle, F. A. (2017) · Scientific Reports · doi:10.1038/s41598-017-11237-6 · Cited by 227 · see citing works
Self-citationSoftware for pre-processing Illumina next-generation sequencing short read sequences
Chen, C., Khaleel, S. S., Huang, H., & Wu, C. H. (2014) · Source Code for Biology and Medicine · doi:10.1186/1751-0473-9-8 · Cited by 221 · see citing works
Designing a transcriptome next‐generation sequencing project for a nonmodel plant species1
Strickler, S. R., Bombarely, A., & Mueller, L. A. (2012) · American Journal of Botany · doi:10.3732/ajb.1100292 · Cited by 222 · see citing works
Trimming of sequence reads alters RNA-Seq gene expression estimates
Williams, C., Baccarella, A., Parrish, J. Z., & Kim, C. C. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-0956-2 · Cited by 217 · see citing works
Wood, S. A., Pochon, X., Laroche, O., von Ammon, U., Adamson, J. E., & Zaiko, A. (2019) · Molecular Ecology Resources · doi:10.1111/1755-0998.13055 · Cited by 216 · see citing works
Environmental DNA enables detection of terrestrial mammals from forest pond water
Ushio, M., Fukuda, H., Inoue, T., Makoto, K., Kishida, O., Sato, K., Murata, K., Nikaido, M., Sado, T., Sato, Y., et al. (2017) · Molecular Ecology Resources · doi:10.1111/1755-0998.12690 · Cited by 214 · see citing works
Rismani‐Yazdi, H., HAZNEDAROĞLU, B. Z., Hsin, C., & Peccia, J. (2012) · Biotechnology for Biofuels · doi:10.1186/1754-6834-5-74 · Cited by 213 · see citing works
On the optimal trimming of high-throughput mRNA sequence data
MacManes, M. D. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00013 · Cited by 211 · see citing works
Origin and adaptation to high altitude of Tibetan semi-wild wheat
Guo, W., Xin, M., Wang, Z., Yao, Y., Hu, Z., Song, W., Yu, K., Chen, Y., Wang, X., Guan, P., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18738-5 · Cited by 208 · see citing works
Vavourakis, C. D., Ghai, R., Rodríguez‐Valera, F., Sorokin, D. Y., Tringe, S. G., Hugenholtz, P., & Gerard Muyzer, C. (2016) · Frontiers in Microbiology · doi:10.3389/fmicb.2016.00211 · Cited by 206 · see citing works
HTQC: a fast quality control toolkit for Illumina sequencing data
Yang, X., Liu, D., Liu, F., Wu, J., Zou, J., Xiao, X., Zhao, F., & Zhu, B. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-33 · Cited by 196 · see citing works
MOCAT: A Metagenomics Assembly and Gene Prediction Toolkit
Kultima, J. R., Sunagawa, S., Li, J., Chen, W., Chen, H., Mende, D. R., Arumugam, M., Pan, Q., Liu, B., Qin, J., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0047656 · Cited by 199 · see citing works
Berens, A. J., Hunt, J. H., & Toth, A. L. (2014) · Molecular Biology and Evolution · doi:10.1093/molbev/msu330 · Cited by 198 · see citing works
Fungal endophyte infection of ryegrass reprograms host metabolism and alters development
Dupont, P., Eaton, C. J., Wargent, J. J., Fechtner, S., Solomon, P. S., Schmid, J., Day, R. C., Scott, B., & Cox, M. P. (2015) · New Phytologist · doi:10.1111/nph.13614 · Cited by 198 · see citing works
Self-citationDe Filippis, F., Genovese, A., Ferranti, P., Gilbert, J. A., & Ercolini, D. (2016) · Scientific Reports · doi:10.1038/srep21871 · Cited by 196 · see citing works
High Temporal-Resolution Transcriptome Landscape of Early Maize Seed Development
Yi, F., Gu, W., Chen, J., Song, N., Gao, X., Zhang, X., Zhou, Y., Ma, X., Song, W., Zhao, H., et al. (2019) · The Plant Cell · doi:10.1105/tpc.18.00961 · Cited by 193 · see citing works
Measuring the activity of protein variants on a large scale using deep mutational scanning
Fowler, D. M., Stephany, J. J., & Fields, S. (2014) · Nature Protocols · doi:10.1038/nprot.2014.153 · Cited by 190 · see citing works
SAR11 bacteria linked to ocean anoxia and nitrogen loss
Tsementzi, D., Wu, J., Deutsch, S., Nath, S., Rodriguez‐R, L. M., Burns, A. S., Ranjan, P., Sarode, N., Malmstrom, R. R., Padilla, C. C., et al. (2016) · Nature · doi:10.1038/nature19068 · Cited by 185 · see citing works
Diet influences the functions of the human intestinal microbiome
Angelis, M. D., Ferrocino, I., Calabrese, F. M., Filippis, F. D., Cavallo, N., Siragusa, S., Rampelli, S., Cagno, R. D., Rantsiou, K., Vannini, L., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-61192-y · Cited by 177 · see citing works
Microbial community successional patterns in beach sands impacted by the Deepwater Horizon oil spill
Rodriguez‐R, L. M., Overholt, W. A., Hagan, C., Huettel, M., Kostka, J. E., & Konstantinidis, K. T. (2015) · The ISME Journal · doi:10.1038/ismej.2015.5 · Cited by 177 · see citing works
Evolution of the bamboos (Bambusoideae; Poaceae): a full plastome phylogenomic analysis
Wysocki, W. P., Clark, L. G., Attigala, L., Ruíz-Sánchez, E., & Duvall, M. R. (2015) · BMC Evolutionary Biology · doi:10.1186/s12862-015-0321-5 · Cited by 176 · see citing works
Oh, S., Hammes, F., & Liu, W. (2017) · Water Research · doi:10.1016/j.watres.2017.10.054 · Cited by 161 · see citing works
Rhizosphere microbiome metagenomics of gray mangroves (Avicennia marina) in the Red Sea
Alzubaidy, H., Essack, M., Malas, T. B., Bokhari, A., Motwalli, O., Kamanu, F., Jamhor, S. A., Mokhtar, N. A., Antunes, A., Simões, M. F., et al. (2015) · Gene · doi:10.1016/j.gene.2015.10.032 · Cited by 157 · see citing works
Li, J., Zhu, L., Hull, J. J., Liang, S., Daniell, H., Jin, S., & Zhang, X. (2016) · Plant Biotechnology Journal · doi:10.1111/pbi.12554 · Cited by 157 · see citing works
Zhang, M., Xie, S., Dong, X., Zhao, X., Zeng, B., Chen, J., Li, H., Yang, W., Zhao, H., Wang, G., et al. (2013) · Genome Research · doi:10.1101/gr.155879.113 · Cited by 157 · see citing works
Zhang, K., Wang, R., Zi, H., Li, Y., Cao, X., Li, D., Guo, L., Tong, J., Pan, Y., Jiao, Y., et al. (2018) · The Plant Cell · doi:10.1105/tpc.17.00705 · Cited by 151 · see citing works
Genome sequencing of the important oilseed crop Sesamum indicumL
Zhang, H., Miao, H., Wang, L., Qu, L., Liu, H., Wang, Q., & Yue, M. (2013) · Genome biology · doi:10.1186/gb-2013-14-1-401 · Cited by 150 · see citing works
Orellana, L. H., Chee‐Sanford, J. C., Sanford, R. A., Löffler, F. E., & Konstantinidis, K. T. (2017) · Applied and Environmental Microbiology · doi:10.1128/aem.01646-17 · Cited by 149 · see citing works
Fujii, K., Doi, H., Matsuoka, S., Nagano, M., Sato, H., & Yamanaka, H. (2019) · PLoS ONE · doi:10.1371/journal.pone.0210357 · Cited by 146 · see citing works
Younus, F., Chertemps, T., Pearce, S. L., Pandey, G., Bozzolan, F., Coppin, C. W., Russell, R. J., Maı̈bèche, M., & Oakeshott, J. G. (2014) · Insect Biochemistry and Molecular Biology · doi:10.1016/j.ibmb.2014.07.003 · Cited by 145 · see citing works
Uropathogenic Escherichia coli Releases Extracellular Vesicles That Are Associated with RNA
Blenkiron, C., Simonov, D., Muthukaruppan, A., Tsai, P., Dauros‐Singorenko, P., Green, S., Hong, J., Print, C. G., Swift, S., & Phillips, A. R. J. (2016) · PLoS ONE · doi:10.1371/journal.pone.0160440 · Cited by 145 · see citing works
The TOR–EIN2 axis mediates nuclear signalling to modulate plant growth
Fu, L., Liu, Y., Qin, G., Wu, P., Zi, H., Xu, Z., Zhao, X., Wang, Y., Li, Y., Yang, S., et al. (2021) · Nature · doi:10.1038/s41586-021-03310-y · Cited by 145 · see citing works
Shotgun Metagenomics and Volatilome Profile of the Microbiota of Fermented Sausages
Ferrocino, I., Bellio, A., Giordano, M., Macori, G., Romano, A., Rantsiou, K., Decastelli, L., & Cocolin, L. (2017) · Applied and Environmental Microbiology · doi:10.1128/aem.02120-17 · Cited by 144 · see citing works
Breaking Free: The Genomics of Allopolyploidy-Facilitated Niche Expansion in White Clover
Griffiths, A. G., Moraga, R., Tausen, M., Gupta, V., Bilton, T. P., Campbell, M. A., Ashby, R., Nagy, I., Khan, A. K., Larking, A. C., et al. (2019) · The Plant Cell · doi:10.1105/tpc.18.00606 · Cited by 141 · see citing works
Self-citationQian, X., Gunturu, S., Guo, J., Chai, B., Cole, J. R., Gu, J., & Tiedje, J. M. (2021) · Microbiome · doi:10.1186/s40168-021-01047-4 · Cited by 140 · see citing works
Minich, J. J., Morris, M. M., Brown, M., Doane, M. P., Edwards, M. S., Michael, T. P., & Dinsdale, E. A. (2018) · PLoS ONE · doi:10.1371/journal.pone.0192772 · Cited by 135 · see citing works
Large-scale phylogenomic analysis resolves a backbone phylogeny in ferns
Shen, H., Jin, D., Shu, J., Zhou, X., Lei, M., Wei, R., Shang, H., Wei, H., Zhang, R., Liu, L., et al. (2017) · GigaScience · doi:10.1093/gigascience/gix116 · Cited by 139 · see citing works
Palacios, T., Vitetta, L., Coulson, S., Madigan, C. D., Lam, Y. Y., Manuel, R., Briskey, D. R., Hendy, C., Kim, J.-N., Ishoey, T., et al. (2020) · Nutrients · doi:10.3390/nu12072041 · Cited by 143 · see citing works
Worm Burden-Dependent Disruption of the Porcine Colon Microbiota by Trichuris suis Infection
Wu, S., Li, R. W., Li, W., Beshah, E., Dawson, H. D., & Urban, J. F. (2012) · PLoS ONE · doi:10.1371/journal.pone.0035470 · Cited by 137 · see citing works
Phylogenomics of the plant family Araceae
Henriquez, C. L., Arias, T., Pires, J. C., Croat, T. B., & Schaal, B. A. (2014) · Molecular Phylogenetics and Evolution · doi:10.1016/j.ympev.2014.02.017 · Cited by 135 · see citing works
Okutman, Ö., Muller, J., Baert, Y., Serdarogullari, M., Gültomruk, M., Piton, A., Rombaut, C., Benkhalifa, M., Teletin, M., Skory, V., et al. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv290 · Cited by 131 · see citing works
Lv, Y., Liang, Z., Ge, M., Qi, W., Zhang, T., Lin, F., Peng, Z., & Zhao, H. Q. (2016) · BMC Genomics · doi:10.1186/s12864-016-2650-1 · Cited by 131 · see citing works
Johnston, E. R., Hatt, J. K., He, Z., Wu, L., Guo, X. Y., Luo, Y., Schuur, E. A. G., Tiedje, J. M., Zhou, J. Z., & Konstantinidis, K. T. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1901307116 · Cited by 130 · see citing works
Single-Cell Transcriptomics Bioinformatics and Computational Challenges
Poirion, O., Zhu, X., Ching, T. H., & Garmire, L. X. (2016) · Frontiers in Genetics · doi:10.3389/fgene.2016.00163 · Cited by 125 · see citing works
Demonstration of the potential of environmental DNA as a tool for the detection of avian species
Ushio, M., Murata, K., Sado, T., Nishiumi, I., Takeshita, M., Iwasaki, W., & Miya, M. U. (2018) · Scientific Reports · doi:10.1038/s41598-018-22817-5 · Cited by 127 · see citing works
Abiotic Stresses Shift Belowground Populus -Associated Bacteria Toward a Core Stress Microbiome
Timm, C. M., Carter, K., Carrell, A. A., Jun, S., Jawdy, S. S., Vélez, J. M., Gunter, L. E., Yang, Z. K., Nookaew, I., Engle, N. L., et al. (2018) · mSystems · doi:10.1128/msystems.00070-17 · Cited by 127 · see citing works
Gao, L., Tu, Z. J., Millett, B. P., & Bradeen, J. M. (2013) · BMC Genomics · doi:10.1186/1471-2164-14-340 · Cited by 124 · see citing works
Francisci, D. D., Kougias, P., Treu, L., Campanaro, S., & Angelidaki, İ. (2014) · Bioresource Technology · doi:10.1016/j.biortech.2014.10.126 · Cited by 125 · see citing works
Quality filtering of Illumina index reads mitigates sample cross-talk
Wright, E. S., & Vetsigian, K. (2016) · BMC Genomics · doi:10.1186/s12864-016-3217-x · Cited by 125 · see citing works
A beginners guide to SNP calling from high-throughput DNA-sequencing data
Altmann, A., Weber, P., Bader, D. M., Preuss, M. H., Binder, E. B., & Müller-Myhsok, B. (2012) · Human Genetics · doi:10.1007/s00439-012-1213-z · Cited by 125 · see citing works
Larriba, E., Jaime, M., Carbonell‐Caballero, J., Conesa, A., Dopazo, J., Nislow, C., Martín‐Nieto, J., & Lopez-Llorca, L. V. (2014) · Fungal Genetics and Biology · doi:10.1016/j.fgb.2014.02.002 · Cited by 124 · see citing works
Rajagopala, S. V., Yooseph, S., Harkins, D. M., Moncera, K. J., Zabokrtsky, K. B., Torralba, M., Tovchigrechko, A., Highlander, S. K., Pieper, R., Sender, L. S., et al. (2016) · BMC Genomics · doi:10.1186/s12864-016-2965-y · Cited by 125 · see citing works
L_RNA_scaffolder: scaffolding genomes with transcripts
Xue, W., Li, J.-T., Zhu, Y., Hou, G., Kong, X., Kuang, Y., & Sun, X. (2013) · BMC Genomics · doi:10.1186/1471-2164-14-604 · Cited by 122 · see citing works
Cernava, T., Erlacher, A., Soh, J., Sensen, C. W., Grube, M., & Berg, G. (2019) · Microbiome · doi:10.1186/s40168-019-0624-7 · Cited by 121 · see citing works
van Veldhoven, K., Polidoro, S., Baglietto, L., Severi, G., Sacerdote, C., Panico, S., Mattiello, A., Palli, D., Masala, G., Krogh, V., et al. (2015) · Clinical Epigenetics · doi:10.1186/s13148-015-0104-2 · Cited by 120 · see citing works
Toda, T., Hsu, J. Y., Linker, S. B., Hu, L., Schafer, S. T., Mertens, J., Jacinto, F. V., Hetzer, M. W., & Gage, F. H. (2017) · Cell stem cell · doi:10.1016/j.stem.2017.08.012 · Cited by 119 · see citing works
Powell, J. J., Fitzgerald, T. L., Stiller, J., Berkman, P. J., Gardiner, D. M., Manners, J. M., Henry, R. J., & Kazan, K. (2016) · Plant Biotechnology Journal · doi:10.1111/pbi.12651 · Cited by 118 · see citing works
Wang, J.-T., Li, J.-T., Zhang, X., & Sun, X. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-96 · Cited by 116 · see citing works
Systematic Error in Seed Plant Phylogenomics
Zhong, B., Deusch, O., Goremykin, V. V., Penny, D., Biggs, P. J., Atherton, R. A., Nikiforova, S. V., & Lockhart, P. J. (2011) · Genome Biology and Evolution · doi:10.1093/gbe/evr105 · Cited by 118 · see citing works
Self-citationComparison of alignment software for genome-wide bisulphite sequence data
Chatterjee, A., Stockwell, P. A., Rodger, E. J., & Morison, I. M. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks150 · Cited by 117 · see citing works
Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine
Elsik, C. G., Tayal, A., Diesh, C. M., Unni, D. R., Emery, M. L., Nguyen, H. N., & Hagen, D. E. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1208 · Cited by 113 · see citing works
Buffa, J. A., Romano, K. A., Copeland, M. F., Cody, D. B., Zhu, W., Galvez, R., Fu, X., Ward, K., Ferrell, M., Dai, H. J., et al. (2021) · Nature Microbiology · doi:10.1038/s41564-021-01010-x · Cited by 114 · see citing works
Optimizing de novo common wheat transcriptome assembly using short-read RNA-Seq data
Duan, J., Xia, C., Zhao, G., Jia, J., & Kong, X. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-392 · Cited by 112 · see citing works
The S phagnum microbiome supports bog ecosystem functioning under extreme conditions
Bragina, A., Oberauner‐Wappis, L., Zachow, C., Halwachs, B., Thallinger, G., Müller, H., & Berg, G. (2014) · Molecular Ecology · doi:10.1111/mec.12885 · Cited by 110 · see citing works
- Authors
- Cox, M. P., Peterson, D. A., & Biggs, P. J.
- Affiliations
- Massey University (NZ)
- Corresponding author
- Cox, Murray P
- Venue
- BMC Bioinformatics
- Published
- 2010-09-27
- Volume
- 11
- Issue
- 1
- Pages
- 485-485
- ISSN
- 1471-2105 (ISSN-L)
- PMC
- PMC2956736
- OpenAlex
- W2097205777
- Cited by
- 1,357
- References
- 9
- Citations by year
- 2026: 29 · 2025: 50 · 2024: 57 · 2023: 86 · 2022: 86 · 2021: 131 · 2020: 118 · 2019: 118 · 2018: 135 · 2017: 105 · 2016: 148 · 2015: 95 · 2014: 97 · 2013: 56 · 2012: 37
- FWCI
- 13.30
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Bioinformatics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Royal Society
- Royal Society Te Apārangi (MAU0802)
- Massey University
- Marsden Fund (MAU0802)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genetics, Bioinformatics, and Biomedical Research
- Keywords
- sequence trimming, quality control software
- MeSH terms
- Base Sequence, Software, Sequence Analysis, DNA, Sequence Analysis, RNA, Internet
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
