在过去的二十年中，广泛的研究，特别是通过癌症基因组图谱 (TCGA) 等大型数据集进行的癌症分析，旨在改善患者治疗和精准医疗。然而，不同群体的基因特征之间有限的重叠和不一致带来了挑战。转录组的动态性质，包括不同的 RNA 种类以及基因和亚型水平的功能复杂性，引入了复杂性，并且由于每个患者独特的转录组景观，当前的基因特征面临重现性问题。在这种背景下，不同测序技术、数据分析算法和软件工具产生的差异进一步阻碍了一致性。虽然仔细的实验​​设计、分析策略和标准化方案可以提高重现性，但未来的前景在于多组学数据集成、机器学习技术、开放科学实践和协作努力。标准化指标、质量控制措施和单细胞 RNA 测序的进步将有助于公正的基因特征识别。在这篇观点文章中，我们概述了一些应对挑战、标准化实践和先进方法的想法和见解，以增强疾病转录组研究中基因特征的可靠性。版权所有：© 2024 Liu 等人。这是一篇根据知识共享署名许可条款分发的开放获取文章，允许在任何媒体上不受限制地使用、分发和复制，前提是注明原始作者和来源。

Over the past two decades, extensive studies, particularly in cancer analysis through large datasets like The Cancer Genome Atlas (TCGA), have aimed at improving patient therapies and precision medicine. However, limited overlap and inconsistencies among gene signatures across different cohorts pose challenges. The dynamic nature of the transcriptome, encompassing diverse RNA species and functional complexities at gene and isoform levels, introduces intricacies, and current gene signatures face reproducibility issues due to the unique transcriptomic landscape of each patient. In this context, discrepancies arising from diverse sequencing technologies, data analysis algorithms, and software tools further hinder consistency. While careful experimental design, analytical strategies, and standardized protocols could enhance reproducibility, future prospects lie in multiomics data integration, machine learning techniques, open science practices, and collaborative efforts. Standardized metrics, quality control measures, and advancements in single-cell RNA-seq will contribute to unbiased gene signature identification. In this perspective article, we outline some thoughts and insights addressing challenges, standardized practices, and advanced methodologies enhancing the reliability of gene signatures in disease transcriptomic research.Copyright: © 2024 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.