SeqKit2: A Swiss army knife for sequence and alignment processing

Abstract

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.

How low can you go? Short-read polishing of Oxford Nanopore bacterial genome assemblies

“…A combination of Pypolca-careful and Polypolish depending on estimated short-read depth has been implemented in our automated assembly tool Hybracter from v0.7.0 [ 15 ]. Depth is estimated inside Hybracter with Seqkit [ 23 24 ] based on the chromosome size parameter estimate provided by the user. Consistent with these results, when the automated ONT-only assembly did not have structural errors [ 25 ], running Hybracter on the benchmarked genomes was consistently able to produce polished assemblies that were error-free above 25× depth, and sometimes at lower depth (Fig.…”

Evidence of RNA polymerase III recruitment and transcription at protein-coding gene promoters

“…Subsequently, we utilized genomecov from BEDtools 48 to create the 3’ pileup of reads across the genome, employing the flags “-dz −3”. T4 motifs (TTTT) were identified within the hg38 genome using SeqKit 49 , with a 3-nt cushion applied on either side of the T4 motif, resulting in a 10-nt long T4 motif. Employing the same scoring method utilized for the occupancy score of 50-nt bins, we computed the T4 score, this time focusing on the 10-nt T4 motif with expected signal over two vicinities: 20 nt and 50 nt on either side of the T4 motif.…”

MATEdb2, a collection of high-quality metazoan proteomes across the Animal Tree of Life to speed up phylogenomic studies

“…The software included is the following: SRA Toolkit v2. Challis et al, 2020)., NCBI datasets v13.42.0, eggNOG-mapper v2.1.9 (Cantalapiedra et al, 2021), seqkit v2.1.0 (Shen, Sipos, andZhao, 2024), AGAT v0.9.1 (Daniat et al, 2023), as well as some custom scripts.…”

“…The software included is the following: SRA Toolkit v2.10.7 (http://ncbi.github.io/sra-tools/), fastp v0.20.1 (https://github.com/OpenGene/fastp; Chen et al, 2018), Trinity v2.11.0 (Grabherr et al 2011), BUSCO v5.3.2 (Manni et al, 2021), TransDecoder v5.5.0 (https://github.com/TransDecoder/TransDecoder), Diamond v2.0.8 (Buchfink, Xie, & Huson, 2015), BlobTools v2.3.3 (Challis et al, 2020). , NCBI datasets v13.42.0, eggNOG-mapper v2.1.9 (Cantalapiedra et al, 2021), seqkit v2.1.0 (Shen, Sipos, and Zhao, 2024), AGAT v0.9.1 (Daniat et al, 2023), as well as some custom scripts.…”