异种移植模型是一种有吸引力的模型，它模仿人类肿瘤生物学并允许扰乱肿瘤微环境并研究其药物反应。空间解析转录组学 (SRT) 提供了一种研究异种移植模型组织的强大方法，但目前缺乏用于处理源自 SRT 实验的异种移植读取的专门流程。 Xenomake 是一个独立的管道，用于自动处理空间异种移植读取。 Xenomake 处理读取处理、对齐、异种移植读取排序，并与下游空间分析包良好连接。我们还表明，Xenomake 可以正确分配生物体特定读数，通过增加基因计数来减少数据稀疏性，同时保持研究的生物学相关性。补充数据可在生物信息学在线获取。© 作者 2024。由牛津大学出版社出版。

Xenograft models are attractive models that mimic human tumor biology and permit one to perturb the tumor microenvironment and study its drug response. Spatially resolved transcriptomics (SRT) provide a powerful way to study the organization of xenograft models, but currently there is a lack of specialized pipeline for processing xenograft reads originated from SRT experiments. Xenomake is a standalone pipeline for the automated handling of spatial xenograft reads. Xenomake handles read processing, alignment, xenograft read sorting, and connects well with downstream spatial analysis packages. We additionally show that Xenomake can correctly assign organism specific reads, reduce sparsity of data by increasing gene counts, while maintaining biological relevance for studies.Supplementary data are available at Bioinformatics online.© The Author(s) 2024. Published by Oxford University Press.