Faculty of Medicine and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg University, Heidelberg, Germany.
GSK, Cellzome, Heidelberg, Germany.
Nat Cell Biol. 2024 Sep;26(9):1613-1622. doi: 10.1038/s41556-024-01469-w. Epub 2024 Sep 2.
The growing availability of single-cell and spatially resolved transcriptomics has led to the development of many approaches to infer cell-cell communication, each capturing only a partial view of the complex landscape of intercellular signalling. Here we present LIANA+, a scalable framework built around a rich knowledge base to decode coordinated inter- and intracellular signalling events from single- and multi-condition datasets in both single-cell and spatially resolved data. By extending and unifying established methodologies, LIANA+ provides a comprehensive set of synergistic components to study cell-cell communication via diverse molecular mediators, including those measured in multi-omics data. LIANA+ is accessible at https://github.com/saezlab/liana-py with extensive vignettes ( https://liana-py.readthedocs.io/ ) and provides an all-in-one solution to intercellular communication inference.
单细胞和空间分辨转录组学的可用性不断增加,导致了许多推断细胞间通讯的方法的发展,每种方法都只能捕捉到细胞间信号复杂景观的部分视图。在这里,我们提出了 LIANA+,这是一个围绕丰富知识库构建的可扩展框架,用于从单细胞和空间分辨数据中单条件和多条件数据集解码协调的细胞内和细胞间信号事件。通过扩展和统一现有的方法,LIANA+提供了一套全面的协同组件,用于通过多种分子介质(包括在多组学数据中测量的介质)研究细胞间通讯。LIANA+可在 https://github.com/saezlab/liana-py 上访问,其中包含大量示例( https://liana-py.readthedocs.io/ ),并提供了一种用于细胞间通讯推断的一体化解决方案。