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Dataset . 2022
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Additional files of scTensor paper "scTensor detects many-to-many cell-cell interactions from single cell RNA-sequencing data"

Authors: Tsuyuzaki, Koki;

Additional files of scTensor paper "scTensor detects many-to-many cell-cell interactions from single cell RNA-sequencing data"

Abstract

Complex biological systems are described as a multitude of cell-cell interactions (CCIs). Recent single-cell RNA-sequencing studies focus on CCIs based on ligand-receptor (L-R) gene co-expression. However, the analytical methods are still not mature; such methods cannot detect CCIs and the related L-R pairs simultaneously or also are not appropriate to detect many-to-many CCIs. In this work, we propose scTensor, a novel method for extracting representative triadic relationships (or hypergraphs), which include ligand-expression, receptor-expression, and related L-R pairs. Through extensive studies with simulated and empirical datasets, we have shown that scTensor could detect some hypergraphs, which cannot be detected by conventional methods, especially when those CCIs are many-to-many relationships.

Related Organizations
Keywords

Single-cell RNA-sequencing, R/Bioconductor, Hypergraph, Tensor Decomposition, Cell-cell interaction, Non-negative Tucker2 Decomposition, Dimension Reduction

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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