Pathway enrichment analysis and visualization for Single Cell Data
NOTE: on a fresh installation, users may need to install some required interpreter compilers for the system to install other R packages:
Install Dependent Packages:
- Some packages require to be installed from sources that need compilation and a proper version of RTools.
- It’s recommended to install devtools, and BiocManager packages first, to install the following packages in Github / Bioconductor (not in CRAN).
# install required packages
install.packages('Seurat') # RStudio may need a RESTART for Seurat v5.0.1 to be activated
install.packages('remotes')
install.packages('waiter')
install.packages('farver')
remotes::install_github('vqv/ggbiplot')
# install CellEnrich
remotes::install_github('noobCoding/CellEnrich')# Download data, if not downloaded
download.file('https://github.com/noobcoding/CellEnrich/raw/master/data/pbmcData.RData','pbmcData.RData', mode = 'wb')
download.file('https://github.com/noobcoding/CellEnrich/raw/master/data/pbmcClustInfo.RData','pbmcClustInfo.RData', mode = 'wb')
download.file('https://github.com/noobcoding/CellEnrich/raw/master/data/Human_Reactome.RData', 'Human_Reactome.RData', mode = 'wb')
# Load library and data
library(CellEnrich)
library(Seurat)
load("pbmcData.RData")
load("pbmcClustInfo.RData")
CountData <- pbmcData
GroupInfo <- pbmcClustInfo
# CellEnrich uses normalized count data as input
CountData <- NormalizeData(CountData)
# This will run CellEnrich
CellEnrich(CountData, GroupInfo)# Download Alzheimer's data to the working directory
download.file('https://github.com/noobcoding/CellEnrich/raw/master/data/Alzheimer_Counts_sampled.RDS','Alzheimer_Counts_sampled.RDS', mode = 'wb')
download.file('https://github.com/noobcoding/CellEnrich/raw/master/data/Alzheimer_CellType_sampled.RDS','Alzheimer_CellType_sampled.RDS', mode = 'wb')
download.file('https://github.com/noobcoding/CellEnrich/raw/master/data/Human_Reactome.RData', 'Human_Reactome.RData', mode = 'wb')
# Load library and data
library(CellEnrich)
library(Seurat)
GroupInfo <- readRDS("Alzheimer_CellType_sampled.RDS")
CountData <- readRDS("Alzheimer_Counts_sampled.RDS")
# CellEnrich uses normalized count data as input
CountData <- NormalizeData(CountData)
# Run cellenrich
CellEnrich(CountData, GroupInfo)# download minimal data to the working directory
download.file('https://github.com/noobcoding/CellEnrich/raw/master/data/LPS_exp.rds','LPS_exp.rds', mode = 'wb')
download.file('https://github.com/noobcoding/CellEnrich/raw/master/data/Mouse_WikiPathways.RData', 'Mouse_WikiPathways.RData', mode = 'wb')
# Load library and data
library(Seurat)
library(CellEnrich)
LPS_exp <- readRDS("LPS_exp.rds")
CountData <- LPS_exp$counts
GroupInfo <- LPS_exp$meta
# CellEnrich uses normalized count data as input
CountData <- NormalizeData(CountData)
# Run cellenrich
CellEnrich(CountData, GroupInfo)
- R - >= 4.2.0
- dplyr - 0.8.5
- DT - 0.13
- farver - 2.0.3
- ggplot2 - 3.3.0
- ggrepel - 0.8.2
- highcharter - 0.7.0.9001
- htmltools - 0.4.0
- magrittr - 1.5
- Rtsne - 0.15
- scales - 1.1.0
- scMerge - 1.5.0
- scran - 1.14.6
- Seurat - 5.0.1
- shiny - 1.4.0.2
- shinyFeedback - 0.2.0
- shinyjs - 1.1
- shinymaterial - 1.0.1
- SingleCellExperiment - 1.8.0
- sortable - 0.4.2
- uwot - 0.1.8
- waiter - 0.1.1.9000*
- Hai Nguyen hainct@unist.ac.kr -- @noobCoding
- Jinhwan Kim @jhk0530
- Prof. Dougu Nam dougnam@unist.ac.kr
This project is MIT licensed