Update README.md

README.md

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 CytoTalk 
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+**Version 3.0.1 (May 12th, 2021)**
+
 Version 2.0 (February 22nd, 2021) 
 
 
 ## Overview
 
 Signal transduction is the primary mechanism for cell-cell communication. scRNA-Seq technology holds great promise for studying cell-cell communication at much higher resolution. Signaling pathways are highly dynamic and cross-talk among them is prevalent. Due to these two features, simply examining expression levels of ligand and receptor genes cannot reliably capture the overall activities of signaling pathways and interactions among them. 
 
-We have developed the CytoTalk algorithm for *de novo* construction of a signaling network (union of multiple signaling pathways emanating from the ligand-receptor pairs) between two cell types using single-cell transcriptomics data. The algorithm first constructs an integrated network consisting of intracellular and intercellular functional gene interactions. It then identifies the signaling network by solving a prize-collecting Steiner forest (PCSF) problem based on appropriately defined node prize (i.e. cell-specific gene activity) and edge cost (i.e. probability of functional interaction between two genes). The objective of the PCSF problem is to find an optimal subnetwork in the integrated network that includes **genes with high levels of cell-type-specific expression and close connection to highly active ligand-receptor pairs**. CytoTalk is currently implemented using a combination of MATLAB (version  R2018a), R (version  3.5.0) and Python (version  3.7.0). 
+We have developed the CytoTalk algorithm for *de novo* construction of a signaling network (union of multiple signaling pathways emanating from the ligand-receptor pairs) between two cell types using single-cell transcriptomics data. The algorithm first constructs an integrated network consisting of intracellular and intercellular functional gene interactions. It then identifies the signaling network by solving a prize-collecting Steiner forest (PCSF) problem based on appropriately defined node prize (i.e. cell-specific gene activity) and edge cost (i.e. probability of functional interaction between two genes). The objective of the PCSF problem is to find an optimal subnetwork in the integrated network that includes **genes with high levels of cell-type-specific expression and close connection to highly active ligand-receptor pairs**. 
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+⚠ **Major update: The latest release "CytoTalk_v3.0.1" is an R version, which is more easily and friendly to use!! Please download the package from the Releases page (https://github.com/huBioinfo/CytoTalk/releases/tag/v3.0.1) and refer to the user manual inside the latest package.** The content below is for the Matlab version "CytoTalk_v2.0". 
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 <div align=center><img src="https://github.com/huBioinfo/CytoTalk/blob/master/CytoTalk_schematic.png" width="60%" height="60%" /></div>
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 ## Packages and Environment configurations      
 
  * The following four **R** packages should be installed (R version  3.5.0 is recommended). 
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 ## Cite CytoTalk  
 
-* Hu Y, Peng T, Gao L, Tan K. CytoTalk: *De novo* construction of signal transduction networks using single-cell RNA-Seq data. *bioRxiv* (2020).
+* Hu Y, Peng T, Gao L, Tan K. CytoTalk: *De novo* construction of signal transduction networks using single-cell transcriptomic data. *Science Advances*, 2021, 7(16): eabf1356.
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+    https://advances.sciencemag.org/content/7/16/eabf1356
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+* Hu Y, Peng T, Gao L, Tan K. CytoTalk: *De novo* construction of signal transduction networks using single-cell RNA-Seq data. *bioRxiv*, 2020.
 
     https://www.biorxiv.org/content/10.1101/2020.03.29.014464v1
 
-* Hu Y, Peng T, Gao L, Tan K. CytoTalk: *De novo* construction of signal transduction networks using single-cell transcriptomics data. *Science Advances* (2021). Accepted.
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 ## Reference  
 
-* Shannon P, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. *Genome Research* 13, 2498-2504 (2003).
+* Shannon P, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. *Genome Research*, 2003, 13: 2498-2504.
 
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