Abstract

The efficient importation of quantified gene expression data is pivotal in transcriptomics. Historically, the R package Tximport addressed this need by enabling seamless data integration from various quantification tools. However, the Python community lacked a corresponding tool, restricting cross-platform bioinformatics interoperability. We introduce Pymportx, a Python adaptation of Tximport, which replicates and extends the original package’s functionalities. Pymportx maintains the integrity and accuracy of gene expression data while improving processing speed and integration within the Python ecosystem. It supports new data formats and includes tools for enhanced data exploration and analysis. Available under the MIT license, Pymportx integrates smoothly with Python’s bioinformatics tools, facilitating a unified and efficient workflow across the R and Python ecosystems. This advancement not only broadens access to Python’s extensive toolset but also fosters interdisciplinary collaboration and the development of cutting-edge bioinformatics analyses.
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Oxford University Press

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Pena González, P., Lozano-Paredes, D., Rojo-Álvarez, J. L., Bote-Curiel, L., & Sánchez-Arévalo Lobo, V. J. (2024). Pymportx: Facilitating next-generation transcriptomics analysis in Python. NAR Genomics and Bioinformatics, 6(4), lqae160. https://doi.org/10.1093/nargab/lqae160

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