Commit fd93d4c9 authored by Leon-Charles Tranchevent's avatar Leon-Charles Tranchevent
Browse files

First version of the scRNA-seq analysis pipeline (up until differential expression).

parent 7ecb2460
INPUT_FOLDER=/home/users/ltranchevent/Data/GeneDER/Original/
OUTPUT_FOLDER=/home/users/ltranchevent/Data/GeneDER/Analysis/09/
CODE_FOLDER=/home/users/ltranchevent/Projects/GeneDER/Analysis/09-Single-cell_analysis/
clean:
@rm -rf *~
clean_outputs:
@rm -rf ${OUTPUT_FOLDER}/*
analyse:
@sbatch ${CODE_FOLDER}analyse.sh
# Objectives
The objectives of this step is to analyse the single-cell data (PD versus control) for male and female samples.
# Details and instructions
# Prerequisites
A prerequisite is to have the scRNA data ready in the project data folder.
\ No newline at end of file
This diff is collapsed.
#!/bin/bash -l
#SBATCH -J geneder:09:scRNA
#SBATCH --mail-type=all
#SBATCH --mail-user=leon-charles.tranchevent@uni.lu
#SBATCH -N 1
#SBATCH --ntasks-per-socket=14
#SBATCH --ntasks-per-node=28
#SBATCH -c 1
#SBATCH --mem=32GB
#SBATCH --time=0-02:00:00
#SBATCH -p batch
#SBATCH --qos=normal
echo "== Starting run at $(date)"
echo "== Job ID: ${SLURM_JOBID}"
echo "== Node list: ${SLURM_NODELIST}"
echo "== Submit dir. : ${SLURM_SUBMIT_DIR}"
echo ""
# Defining global parameters.
OUTPUT_FOLDER=/home/users/ltranchevent/Data/GeneDER/Analysis/09/
CODE_FOLDER=/home/users/ltranchevent/Projects/GeneDER/Analysis/09-Single-cell_analysis/
# Loading modules.
module load lang/R/3.6.2-foss-2019b-bare
# Load configuration
source ../libs/conf/confSH.sh
create_variables ../Confs/datasets_config.yml
# We get the Ensembl and HGNC data
wget -O ${OUTPUT_FOLDER}mitochondrial_genes.tsv 'http://www.ensembl.org/biomart/martservice?query=<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE Query><Query virtualSchemaName = "default" formatter = "TSV" header = "0" uniqueRows = "0" count = "" datasetConfigVersion = "0.6" ><Dataset name = "hsapiens_gene_ensembl" interface = "default" ><Filter name = "chromosome_name" value = "MT"/><Attribute name = "ensembl_gene_id" /></Dataset></Query>'
wget -O ${OUTPUT_FOLDER}ribosomalrna_genes.tsv 'https://www.genenames.org/cgi-bin/genegroup/download?id=848&type=branch'
# For all scRNA datasets
#nbScDatasets=${#scdatasets__dataset_name[@]}
#for (( i=0; i<$nbScDatasets; i++ ))
#do
i=1
datasetName=${scdatasets__dataset_name[$i]}
echo "== Job $i started (${datasetName}) =="
rm -rf ${OUTPUT_FOLDER}${datasetName}/
mkdir ${OUTPUT_FOLDER}${datasetName}/
Rscript --vanilla ${CODE_FOLDER}analyse.R ${datasetName} > ${OUTPUT_FOLDER}${datasetName}/analysis_log.out 2> ${OUTPUT_FOLDER}${datasetName}/analysis_log.err
echo "== Job $i ended (${datasetName}) =="
#done
# Moving the slurm log file to data
mv ${CODE_FOLDER}/slurm-*out ${OUTPUT_FOLDER}/
local_data_dir: !!str '09/'
local_code_dir: !!str '09-Single-cell_analysis/'
......@@ -247,3 +247,8 @@ datasets:
has_age: 'TRUE'
tissue: iPSC-DA
quality_score: 1.0 # Was NA
scdatasets:
-
dataset_name: GSE157783
-
dataset_name: GSE157783s
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