The data and code for paper "Transposable element activation drives human herpesvirus-mediated Alzheimer’s disease".
Data Description
This document contains scripts for analyzing transposable element (TE) expression in bulk and single-cell RNA sequencing (scRNA-seq) datasets. It contains four scripts.
1. HHV RNA screening using bulk RNA-seq data
Software requirement:
- VIRTUS (v2.0.1) (https://github.com/yyoshiaki/VIRTUS2)
Input files
- Sample list, include all the samples to be analyzed
- Raw fastq file directory
How to run
- Single-end RNA-seq data: nohup sh work_VIRTUS.SE.sh sample.lst fastq_dir > log 2>&1 &
- Paired-end RNA-seq data: nohup sh work_VIRTUS.PE.sh sample.lst fastq_dir > log 2>&1 &
2. HHV RNA screening using scRNA-seq data
Software requirement:
- umi_tools (v1.1.2): https://github.com/CGATOxford/UMI-tools
- Viral-Track: https://github.com/PierreBSC/Viral-Track
Input files
- Sample list: include all the samples to be analyzed
- Raw fastq file directory
- Parameters.txt: consists in a list of rows where the name of each variable is followed by an equal symbol and then the value of the parameter
- Target_file.txt: contains the list of the file paths generated by umi_tools. The files can be either .fastq or .fastq.gz files
How to run
- nohup sh 01_umi_tools_work.sh sample.lst fastq_dir > log 2>&1 &
- nohup Rscript Viral_Track_scanning.R ./Parameters.txt ./Target_file.txt > log 2>&1 &
3. Transposable element expression at single-cell level
Software requirement:
- scTE (v1.0.0): https://github.com/JiekaiLab/scTE
- scanpy: https://github.com/scverse/scanpy
Input files
- Sample list, include all the samples to be analyzed
- Raw bam file directory
- Use scTE generated csv.gz files as input files for scanpy
How to run
- nohup sh 0.scTE.sh sample.lst > log 2>&1 &
- nohup python 1.pack.py > log 2>&1 &
- nohup python 2.norm_and_learn.py > log 2>&1 &
- nohup python 3.diffexp_01.py > log1 2>&1 &
- nohup python 3.diffexp_02.py > log2 2>&1 &
4. WGCNA (weighted gene co-expression network analysis)
Software requirement:
Input files
- locusTE_gene_FPKM.txt: This dataset contains expression matrix for each brain biobank. Note that each raw corresponds to a gene or a locus TE and column to a sample
- Metadata.csv: this table contains metadata information for the samples. Note that each raw corresponds to a sample and column to a clinical-pathologic parameter
How to run
- nohup Rscript wgcna_pipeline.R > log 2>&1 &