Bioinformatics Core Unit (BCU), Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany.
Cardio-Pulmonary Institute (CPI), Bad Nauheim, Germany.
Sci Rep. 2024 Jul 6;14(1):15581. doi: 10.1038/s41598-024-66381-7.
In higher organisms, individual cells respond to signals and perturbations by epigenetic regulation and transcriptional adaptation. However, in addition to shifting the expression level of individual genes, the adaptive response of cells can also lead to shifts in the proportions of different cell types. Recent methods such as scRNA-seq allow for the interrogation of expression on the single-cell level, and can quantify individual cell type clusters within complex tissue samples. In order to identify clusters showing differential composition between different biological conditions, differential proportion analysis has recently been introduced. However, bioinformatics tools for robust proportion analysis of both replicated and unreplicated single-cell datasets are critically missing. In this manuscript, we present Scanpro, a modular tool for proportion analysis, seamlessly integrating into widely accepted frameworks in the Python environment. Scanpro is fast, accurate, supports datasets without replicates, and is intended to be used by bioinformatics experts and beginners alike.
在高等生物中，单个细胞通过表观遗传调控和转录适应来响应信号和扰动。然而，细胞的适应性反应不仅可以改变单个基因的表达水平，还可以导致不同细胞类型比例的变化。最近的方法，如 scRNA-seq，允许在单细胞水平上进行表达的检测，并可以定量复杂组织样本中的单个细胞类型簇。为了识别不同生物条件下显示出不同组成的簇，最近引入了差异比例分析。然而，稳健的复制和非复制单细胞数据集比例分析的生物信息学工具却严重缺失。在本文中，我们提出了 Scanpro，这是一个用于比例分析的模块化工具，无缝集成到 Python 环境中广泛接受的框架中。Scanpro 速度快、准确，支持无重复数据集，旨在供生物信息学专家和初学者使用。
