Pympor tx: facilitating next-g ener ation tr anscript omics analysis in Python

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-platf orm bioinf ormatics interoperabilit y. We introduce Pymportx, a Python adapt ation 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 bioinf ormatics tools, f acilitating a unified and efficient w orkflo w across the R and Python ecosy stems. T his adv ancement not only broadens access to Python's e xtensiv e toolset but also f osters interdisciplinary collaboration and the de v elopment of cutting-edge bioinformatics analyses