The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
SeqKit2: A Swiss army knife for sequence and alignment processing
Open accessAbstract
In the era of ubiquitous high‐throughput sequencing studies, there is a growing need for analysis tools that are not just performant but also comprehensive and user‐friendly enough to cater to both novice and advanced users. This article introduces SeqKit2, the next iteration of the widely used sequence analysis tool SeqKit, featuring expanded functionality, performance optimizations, and support for additional compression methods. Retaining a pragmatic subcommand architecture, SeqKit2 represents substantial enhancement through the inclusion of 19 additional subcommands, expanding its overall repertoire to a total of 38 in eight categories. The new subcommands add functionality such as amplicon processing and robust, error‐tolerant parsing of sequence records. In addition, three subcommands designed for real‐time analysis are added for periodic monitoring of properties of FASTQ and Binary Alignment/Map alignment records and real‐time streaming from multiple sequence files. The performance of SeqKit2 is benchmarked against the old version of SeqKit, Bioawk, Seqtk, and SeqFu tools. SeqKit2 consistently outperforms its predecessor, albeit with marginally higher memory usage, while maintaining competitive runtimes against other tools. With its broad functionality, proven usability, and ongoing development driven by user feedback, we hope that bioinformaticians will find SeqKit2 useful as a “Swiss army knife” of sequence and alignment processing—equally adept at facilitating ad hoc analyses and seamlessly integrating into larger pipelines.
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Twelve years of SAMtools and BCFtools
Danecek, P., Bonfield, J. K., Liddle, J., Marshall, J., Ohan, V., Pollard, M. O., Whitwham, A., Keane, T., McCarthy, S. A., Davies, R. M., et al. (2021) · GigaScience · doi:10.1093/gigascience/giab008 · Cited by 15,343
SeqKit: A Cross-Platform and Ultrafast Toolkit for FASTA/Q File Manipulation
Shen, W., Le, S., Li, Y., & Hu, F. (2016) · PLOS ONE · doi:10.1371/journal.pone.0163962 · Cited by 3,380
Self-citationBioStar: An Online Question & Answer Resource for the Bioinformatics Community
Parnell, L. D., Lindenbaum, P., Shameer, K., Dall’Olio, G. M., Swan, D., Jensen, L. J., Cockell, S., Pedersen, B. S., Mangan, M. E., Miller, C. A., et al. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002216 · Cited by 99
SeqFu: A Suite of Utilities for the Robust and Reproducible Manipulation of Sequence Files
Telatin, A., Fariselli, P., & Birolo, G. (2021) · Bioengineering · doi:10.3390/bioengineering8050059 · Cited by 64
Gardner, P. P., Paterson, J. M., McGimpsey, S., Ghomi, F. A., Umu, S. U., Pawlik, A., Gavryushkin, A., & Black, M. A. (2022) · Genome biology · doi:10.1186/s13059-022-02625-x · Cited by 34
Du, L., Liu, Q., Fan, Z., Tang, J., Zhang, X., Price, M., Yue, B., & Zhao, K. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa368 · Cited by 24
Li, G., Shen, W., Gong, Y., Li, M., Rao, X., Liu, Q., Yu, Y., Zhou, J., Zhu, K., Yuan, M., et al. (2022) · mSystems · doi:10.1128/msystems.00338-22 · Cited by 17
Self-citationBigSeqKit: a parallel Big Data toolkit to process FASTA and FASTQ files at scale
Piñeiro, C., & Pichel, J. C. (2022) · GigaScience · doi:10.1093/gigascience/giad062 · Cited by 11
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Shao, Y., Wang, S., Gichuki, B. M., Stares, M. D., Rozday, T. J., Kumar, N., Browne, H. P., Dawson, N. J. R., Njunge, J. M., Tigoi, C., et al. (2026) · Cell · doi:10.1016/j.cell.2026.01.007 · Cited by 17
Sudasinghe, H., Liu, Z., Triginer-Llabrés, L., Hui Tan, H., Britz, R., Salzburger, W., Peichel, C. L., & Rüber, L. (2026) · doi:10.64898/2026.03.21.713365 · Cited by 2
nf-core/proteinfamilies: a scalable pipeline for the generation of protein families
Karatzas, E., Beracochea, M., Baltoumas, F. A., Aplakidou, E., Richardson, L., Fellows Yates, J. A., Lundin, D., community, N.-C., Buluç, A., Kyrpides, N. C., et al. (2026) · GigaScience · doi:10.1093/gigascience/giag009
Metadata
- Authors
- Shen, W., Sipos, B., & Zhao, L.
- Venue
- iMeta
- Publisher
- Wiley
- Published
- 2024-04-05
- Volume
- 3
- Issue
- 3
- Pages
- e191-e191
- ISSN
- 2770-596X (ISSN-L)
- 2770-5986
- OpenAlex
- W4393995158
- Cited by
- 484
- References
- 8
- FWCI
- 56.23
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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