The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
proovread : large-scale high-accuracy PacBio correction through iterative short read consensus
Open accessAbstract
Motivation : Today, the base code of DNA is mostly determined through sequencing by synthesis as provided by the Illumina sequencers. Although highly accurate, resulting reads are short, making their analyses challenging. Recently, a new technology, single molecule real-time (SMRT) sequencing, was developed that could address these challenges, as it generates reads of several thousand bases. But, their broad application has been hampered by a high error rate. Therefore, hybrid approaches that use high-quality short reads to correct erroneous SMRT long reads have been developed. Still, current implementations have great demands on hardware, work only in well-defined computing infrastructures and reject a substantial amount of reads. This limits their usability considerably, especially in the case of large sequencing projects. Results : Here we present proovread , a hybrid correction pipeline for SMRT reads, which can be flexibly adapted on existing hardware and infrastructure from a laptop to a high-performance computing cluster. On genomic and transcriptomic test cases covering Escherichia coli , Arabidopsis thaliana and human, proovread achieved accuracies up to 99.9% and outperformed the existing hybrid correction programs. Furthermore, proovread -corrected sequences were longer and the throughput was higher. Thus, proovread combines the most accurate correction results with an excellent adaptability to the available hardware. It will therefore increase the applicability and value of SMRT sequencing. Availability and implementation: proovread is available at the following URL: http://proovread.bioapps.biozentrum.uni-wuerzburg.de Contact : frank.foerster@biozentrum.uni-wuerzburg.de Supplementary information: Supplementary data are available at Bioinformatics online.
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Cites
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
De novo assembly of human genomes with massively parallel short read sequencing
Li, R., Zhu, H., Ruan, J., Qian, W., Fang, X., Shi, Z., Li, Y., Li, S., Shan, G., Kristiansen, K., et al. (2010) · Genome Research · doi:10.1101/gr.097261.109 · Cited by 2,926 · cited 1×
“Accordingly, a plenitude of short read assemblers has been developed, e.g. Allpath-LG (Gnerre et al., 2011), the Celera Assembler (Myers et al., 2000; Miller et al., 2008), and SOAPdenovo (R. Li et al., 2010).”
MethodSHRiMP2: Sensitive yet Practical Short Read Mapping
David, M., Dzamba, M., Lister, D., Ilie, L., & Brudno, M. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr046 · Cited by 348
Improving PacBio Long Read Accuracy by Short Read Alignment
Au, K. F., Underwood, J. G., Lee, L., & Wong, W. H. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046679 · Cited by 335
Cited by
Sahraeian, S. M. E., Mohiyuddin, M., Sebra, R., Tilgner, H., Afshar, P. T., Au, K. F., Bani Asadi, N., Gerstein, M. B., Wong, W. H., Snyder, M. P., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00050-4 · Cited by 376
Ye, C., Hill, C. M., Wu, S., Ruan, J., & Ma, Z. (2016) · Scientific Reports · doi:10.1038/srep31900 · Cited by 304
A comprehensive evaluation of long read error correction methods
Zhang, H., Jain, C., & Aluru, S. (2020) · BMC Genomics · doi:10.1186/s12864-020-07227-0 · Cited by 150
A reference genome of the Chinese hamster based on a hybrid assembly strategy
Rupp, O., MacDonald, M. L., Li, S., Dhiman, H., Polson, S., Griep, S., Heffner, K., Hernandez, I., Brinkrolf, K., Jadhav, V., et al. (2018) · Biotechnology and Bioengineering · doi:10.1002/bit.26722 · Cited by 107
Schmid, M., Frei, D., Patrignani, A., Schlapbach, R., Frey, J. E., Remus-Emsermann, M. N. P., & Ahrens, C. H. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky726 · Cited by 92
Metadata
- Authors
- Hackl, T., Hedrich, R., Schultz, J., & Förster, F.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-07-10
- Volume
- 30
- Issue
- 21
- Pages
- 3004-3011
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2139306346
- Cited by
- 510
- References
- 4
- FWCI
- 10.10
- Type
- journal article
- Language
- en
- Open access
- green
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