iTALK: an R Package to Characterize and Illustrate Intercellular Communication
By Yuanxin Wang, Ruiping Wang, Shaojun Zhang, Shumei Song, Changying Jiang, Guangchun Han, Michael Wang, J. Ajani, A. Futreal, Linghua Wang. bioRxiv, 2019
298 citations recorded by the source corpus.
Crosstalk between tumor cells and other cells within the tumor microenvironment (TME) plays a crucial role in tumor progression, metastases, and therapy resistance. We present iTALK, a computational approach to characterize and illustrate intercellular communication signals in the multicellular tumor ecosystem using single-cell RNA sequencing data. iTALK can in principle be used to dissect the complexity, diversity, and dynamics of cell-cell communication from a wide range of cellular processes.
Subfields: Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/bd4bb83173a6365b99095bf108f3ddd36ee608af
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In Molecular Biology
Citations in the corpus
- COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas (2021, unknown): “…the possible cell-cell interactions in terms of cytokine storm between the highly inflammation-correlated cell types evaluated by the inflammation score within each tissue and the crosstalk between lung and circulating blood, we employed an R package iTALK introduced by (Wang et al., 2019).”
- SingleCellSignalR: inference of intercellular networks from single-cell transcriptomics (2019, background): “The general characteristics of SingleCellSignalR and re-lated tools appear in Table 1. iTALK (25) infers LR pairs from a compilation of public LR databases using a product score limited to the most abundantly expressed genes.”