ArticleCancers2022
CellCallEXT: Analysis of Ligand-Receptor and Transcription Factor Activities in Cell-Cell Communication of Tumor Immune Microenvironment.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Differential cellular communication inference framework for large-scale single-cell RNA-sequencing data.NAR genomics and bioinformatics · 2025Article
- Single-cell transcriptomics in metastatic breast cancer: mapping tumor evolution and therapeutic resistance.Frontiers in genetics · 2025Review
- Dimension reduction, cell clustering, and cell-cell communication inference for single-cell transcriptomics with DcjComm.Genome biology · 2024Article
- Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
(1) Background: Single-cell RNA sequencing (scRNA-seq) data are useful for decoding cell-cell communication. CellCall is a tool that is used to infer inter- and intracellular communication pathways by integrating paired ligand-receptor (L-R) and transcription factor (TF) activities from steady-state data and thus cannot directly handle two-condition comparisons. For tumor and healthy status, it can only individually analyze cells from tumor or healthy tissue and examine L-R pairs only identified in either tumor or healthy controls, but not both together. Furthermore, CellCall is highly affected by gene expression specificity in tissues. (2) Methods: CellCallEXT is an extension of CellCall that deconvolutes intercellular communication and related internal regulatory signals based on scRNA-seq. Information on Reactome was retrieved and integrated with prior knowledge of L-R-TF signaling and gene regulation datasets of CellCall. (3) Results: CellCallEXT was successfully applied to examine tumors and immune cell microenvironments and to identify the altered L-R pairs and downstream gene regulatory networks among immune cells. Application of CellCallEXT to scRNA-seq data from patients with deficiency of adenosine deaminase 2 demonstrated its ability to impute dysfunctional intercellular communication and related transcriptional factor activities. (4) Conclusions: CellCallEXT provides a practical tool to examine intercellular communication in disease based on scRNA-seq data.
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Registered trials
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