In sqjin/CellChat: Inference and analysis of cell-cell communication from single-cell and spatial transcriptomics data

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title: "Update CellChatDB by adding user-defined ligand-receptor pairs" author: "Suoqin Jin" output: html_document mainfont: Arial vignette: > %\VignetteIndexEntry{Update CellChatDB by adding user-defined ligand-receptor pairs} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8}

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This vignette outlines the steps to update CellChatDB by adding user-defined ligand-receptor pairs. To do so, the format of the users’ lists must be compatible with the input files of CellChatDB. Users can update CellChatDB by submitting their lists via a pull request at Github (https://github.com/sqjin/CellChat) or following the four steps as follows.

Load the required libraries

library(CellChat)
options(stringsAsFactors = FALSE)

Step 1: Access the ligand-receptor interaction information in CellChatDB

Extract the database information in CellChatDB and then save them in a local computer, including four files: 'geneInfo.csv', 'interaction_input_CellChat.csv', 'complex_input_CellChat.csv', 'and cofactor_input_CellChat.csv'. Users can do it by running the following codes in Rstudio:

CellChatDB <- CellChatDB.mouse # set CellChatDB <- CellChatDB.human if working on the human dataset
interaction_input <- CellChatDB$interaction
complex_input <- CellChatDB$complex
cofactor_input <- CellChatDB$cofactor
geneInfo <- CellChatDB$geneInfo
write.csv(interaction_input, file = "interaction_input_CellChatDB.csv")
write.csv(complex_input, file = "complex_input_CellChatDB.csv")
write.csv(cofactor_input, file = "cofactor_input_CellChatDB.csv")
write.csv(geneInfo, file = "geneInfo_input_CellChatDB.csv")

Step 2: Update the required files by adding users’ curated ligand-receptor pairs

Update the above four .csv files by adding users’ curated ligand-receptor pairs.

• The main file is 'interaction_input_CellChatDB.csv'. Users can first update the ligands, receptors and co-factors in the corresponding columns in 'interaction_input_CellChatDB.csv'.

• Users can then update "complex_input_CellChatDB.csv" and "cofactor_input_CellChatDB.csv" if any ligand complex, receptor complex and cofactors are updated. Users need to make sure that user-defined complex/cofactor names are the same in 'interaction_input_CellChatDB.csv' and "complex_input_CellChatDB.csv", 'interaction_input_CellChatDB.csv' and " cofactor_input_CellChatDB.csv".

• "geneInfo_input_CellChatDB.csv" contains all gene information in mouse and it should have a column named ‘Symbol’, which does not need to be changed when updating CellChatDB.

Step 3: Update CellChatDB

Update CellChatDB once updating the four .csv files. Users can do it by running the following codes in Rstudio:

options(stringsAsFactors = FALSE)
interaction_input <- read.csv(file = 'interaction_input_CellChatDB.csv', row.names = 1)
complex_input <- read.csv(file = 'complex_input_CellChatDB.csv', row.names = 1)
cofactor_input <- read.csv(file = 'cofactor_input_CellChatDB.csv', row.names = 1)
geneInfo <- read.csv(file = ' geneInfo_input_CellChatDB.csv', row.names = 1)
CellChatDB <- list()
CellChatDB$interaction <- interaction_input
CellChatDB$complex <- complex_input
CellChatDB$cofactor <- cofactor_input
CellChatDB$geneInfo <- geneInfo

Step 4: Re-build CellChat package (optional)

Re-build CellChat package by updating the database as follows

setwd("/Users/$USERS/Downloads/CellChat-master") # This is the folder of CellChat package downloaded from Github
CellChatDB.mouse <- CellChatDB
usethis::use_data(CellChatDB.mouse, overwrite = TRUE)

# If working on a human dataset, do following:
# CellChatDB.human <- CellChatDB
# usethis::use_data(CellChatDB.human, overwrite = TRUE)

sqjin/CellChat documentation built on Nov. 10, 2023, 4:29 a.m.