sc-seq_hpc/HPC_commands.txt at main · yuanna23/sc-seq_hpc · GitHub

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1.activate my environment:
conda activate my_smu

2.extract tar files: tar -xf GSE154600_RAW.tar

find . -type f -name '*T77*' -print0 | xargs -0 mv -t lustre/work/client/users/
yuannaw/singlecells/T77/

check all the files under the folder----------------ls

3.move files to one folder
mv GSM4816047_barcodes_16030X4_HJTWLDMXX.tsv.gz GSM4816047_features_16030X4_HJTWLDMXX.tsv.gz GSM4816047_matrix_16030X4_HJTWLDMXX.mtx.gz /lustre/work/client/users/yuannaw/singlecells/X4/


10/4/2023
4.convert tsv.gz to tsv-----------gunzip yourfile.tsv.gz
if a folder------------gunzip /path/to/folder/*.gz
(base) yuannaw@m3login04:/lustre/work/client/users/yuannaw/singlecells/T59$ cd /lustre/work/client/users/yuannaw/singlecells

5.change all the names to barcodes.tsv, genes.tsv, matrix.mtx

6. run R language
install.packages("Seurat")
library(Seurat)
library(stringr)
install.packages("remotes")
remotes::install_github("lazappi/clustree@develop")#install package from github
library(clustree)
library(dplyr)
BiocManager::install("GSVA")
library(GSVA)
install.packages("msigdbr")
library(msigdbr)
BiocManager::install("GSEABase")
library(GSEABase)
install.packages("pheatmap")
library(pheatmap)
install.packages("harmony")
library(harmony)
rm(list = ls())
gc()#free up memory
getwd()#show the path
setwd("/lustre/work/client/users/yuannaw/singlecells")
#1.read data from each sample
#test
data_directory <- "/lustre/work/client/users/yuannaw/singlecells/T59"
counts = Read10X(data_directory)
T59_counts<-Read10X(data.dir = "/lustre/work/client/users/yuannaw/singlecells/T59")
T59<-CreateSeuratObject(counts = T59_counts,
                                min.features = 100)
head(T59@meta.data)
#run
for (fileobj in c("T59", "T76","T77","T89","T90","X2","X3","X4")){
  seurat_data <- Read10X(data.dir = paste0("/lustre/work/client/users/yuannaw/singlecells/", fileobj))
  seurat_obj <- CreateSeuratObject(counts = seurat_data,
                                   project = fileobj)
  assign(fileobj, seurat_obj)
}
seurat_obj@project.name
head(T59@meta.data)
head(T76@meta.data)
class(seurat_obj)
# Create a merged Seurat object
seurat_list <- list(T59,T76,T77,T89,T90,X2,X3,X4)
sce<- Reduce(function(x, y) merge(x, y), seurat_list)
dim(sce)
#38224 genes 67323 cells