BioKIT: a versatile toolkit for processing and analyzing diverse types of sequence data

Steenwyk, J. L.; Buida, T. J.; Goncalves, C.; Goltz, D. C.; Morales, G. H.; Mead, M. E.; LaBella, A. L.; Chavez, C. M.; Schmitz, J. E.; Hadjifrangiskou, M.; Li, Y.; Rokas, A.

doi:10.1101/2021.10.02.462868

bioRxiv · 10.1101/2021.10.02.462868

BioKIT: a versatile toolkit for processing and analyzing diverse types of sequence data

Steenwyk, J. L.·Buida, T. J.·Goncalves, C.·Goltz, D. C.·Morales, G. H.·Mead, M. E.·LaBella, A. L.·Chavez, C. M.·Schmitz, J. E.·Hadjifrangiskou, M.·Li, Y.·Rokas, A.

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Abstract

Bioinformatic analysis--such as genome assembly quality assessment, alignment summary statistics, relative synonymous codon usage, paired-end aware quality trimming and filtering of sequencing reads, file format conversion, and processing and analysis--is integrated into diverse disciplines in the biological sciences. Several command-line pieces of software have been developed to conduct some of these individual analyses; however, the lack of a unified toolkit that conducts all these analyses can be a barrier in workflows. To address this obstacle, we introduce BioKIT, a versatile toolkit for the UNIX shell environment with 40 functions, several of which were community-sourced, that conduct routine and novel processing and analysis of genome assemblies, multiple sequence alignments, coding sequences, sequencing data, and more. To demonstrate the utility of BioKIT, we assessed the quality and characteristics of 901 eukaryotic genome assemblies, calculated alignment summary statistics for 10 phylogenomic data matrices, determined relative synonymous codon usage across 171 fungal genomes including those that use alternative genetic codes, and demonstrate that a novel metric, gene-wise relative synonymous codon usage, can accurately estimate gene-wise codon optimization. BioKIT will be helpful in facilitating and streamlining sequence analysis workflows. BioKIT is freely available under the MIT license from GitHub (https://github.com/JLSteenwyk/BioKIT), PyPi (https://pypi.org/project/jlsteenwykbiokit/), and the Anaconda Cloud (https://anaconda.org/jlsteenwyk/jlsteenwyk-biokit). Documentation, user tutorials, and instructions for requesting new features are available online (https://jlsteenwyk.com/BioKIT).

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Steenwyk, J. L., Buida, T. J., Goncalves, C., Goltz, D. C., Morales, G. H., Mead, M. E., LaBella, A. L., Chavez, C. M., Schmitz, J. E., Hadjifrangiskou, M., Li, Y., Rokas, A.. 2021-10-03. BioKIT: a versatile toolkit for processing and analyzing diverse types of sequence data. https://doi.org/10.1101/2021.10.02.462868

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