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Ligand-Receptor Analysis for scRNAseq data

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LigandReceptor

The goal of LigandReceptor is to simplify the process of identifying potential ligand-receptor pairs in scRNAseq data

Installation

You can install LigandReceptor from GitHub with:

# install.packages("devtools")
devtools::install_github("chiblyaa/LigandReceptor")

Example

To use this function, first obtain a list of genes expressed in a scRNAseq dataset using the SEURAT function FindAllMarkers(). An example of an acceptable table:

p_val avg_logFC pct.1 pct.2 p_val_adj cluster gene
Gpx2 0 1.4570746 0.858 0.069 0 End bud Gpx2
Aldoc 0 1.1354879 0.750 0.091 0 End bud Aldoc
Tmem54 0 0.4738690 0.549 0.038 0 End bud Tmem54
S100a14 0 0.3989609 0.424 0.025 0 End bud S100a14
Bex4 0 0.9329017 0.805 0.125 0 End bud Bex4

Basic example code for generating a table with ligand-receptor pairs:

library(LigandReceptor)
#> 
#> Attaching package: 'LigandReceptor'
#> The following object is masked _by_ '.GlobalEnv':
#> 
#>     test_dataset
## This will generate a table with ligand-receptor pair for the specified cell types in celltypelabels
LR.pairs <- LigandReceptorPairsTable(seuratDEGS = test_dataset, LRdatabase = LRdatabase)
knitr::kable(LR.pairs[1:10,], caption = "Ligand-Receptor pairs: ")
from to value pairs
End bud End bud 14 Tnc_sdc4, Lamc2_itgb4, Lamc2_itga6, Lamc2_col17a1, Lamc2_cd151, Lamb3_col17a1, Lamb3_cd151, Lamb3_itga6, Lamb3_itgb4, Lama5_itga6, Lama5_itgb4, Lama5_bcam, Hbegf_cd9, Cdh1_ptprf
Krt19+ duct End bud 1 Cdh1_ptprf
Basal duct End bud 4 Thbs1_sdc4, Thbs1_itga6, Hbegf_cd9, Cdh1_ptprf
Myoepithelial End bud 1 Gnai2_f2r
Macrophages End bud 20 Thbs1_sdc4, Thbs1_itga6, Tgm2_sdc4, Mdk_sdc4, Mdk_itga6, Lamc2_itgb4, Lamc2_itga6, Lamc2_col17a1, Lamc2_cd151, Lamc1_itgb4, Lamc1_itga6, Lamb3_col17a1, Lamb3_cd151, Lamb3_itga6, Lamb3_itgb4, Lamb1_itga6, Lamb1_itgb4, Lama5_itga6, Lama5_itgb4, Lama5_bcam
Stromal End bud 24 Tnfsf12_tnfrsf12a, Thbs2_itga6, Thbs1_sdc4, Thbs1_itga6, Tfpi_f3, Tfpi_sdc4, Rspo3_sdc4, Rspo3_lgr4, Nid1_ptprf, Mdk_sdc4, Mdk_itga6, Lamc1_itgb4, Lamc1_itga6, Lamb1_itga6, Lamb1_itgb4, Lama4_itga6, Lama2_itgb4, Lama2_itga6, Lama2_rpsa, Gnai2_f2r, Fn1_itga6, Cxcl12_sdc4, Col6a1_itga6, Adam12_sdc4
End bud Krt19+ duct 2 Hbegf_cd9, Cdh1_ptprf
Krt19+ duct Krt19+ duct 3 Cdh1_ptprf, Calm1_hmmr, Calm1_kcnn4
Basal duct Krt19+ duct 2 Hbegf_cd9, Cdh1_ptprf
Myoepithelial Krt19+ duct 2 Calm1_hmmr, Calm1_kcnn4

Chord plot to represent ligands from Myoepithelial cells to all other cells:

# This will generate the chord plot associated with the table
colors = topo.colors(as.numeric(length(unique(test_dataset$cluster)))) # create vector of colors of length = ncells
names(colors) <- as.character(unique(test_dataset$cluster))

PairsPlot(cellcolors=colors, seuratDEGS = test_dataset, LRdatabase)
legend("bottomright",   # location of legend
      legend = names(colors), # categories or elements to render in
             # the legend
      fill = colors) 

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