This repository utilizes Nextflow to create a reproducable bioinformatics pipeline for RNA sequencing analysis using STAR, RSEM and/or Salmon with gene counts and extensive quality control.
The pipeline takes FASTQ files as input, performs initial MD5 checks, quality control (QC) checks, trimming, and alignment, and produces a gene expression matrix, QC reports, and gene set enrichment data.
- 1a. Get FASTQ data from Dropbox and move it to the HPC (
get_dropbox_data-<PI_NAME>.nf) - 1b. Check the MD5 Checksum values of the transferred data (
check_md5.py) - 2a. Update Wormbase GeneIDs based on Version Number (e.g.,WS289) (
utility/wormbase_download.sh,create_star_rsem_index.nf,create_salmon_index.nf) - 2b. Get genome/transcript data from Wormbase for alignment (
utility/wormbase_download.sh) - 3a. Create STAR and rsem indexes (
create_star_rsem_index.nf) - 3b. Create Salmon index file (
create_salmon_index.nf)- NOTE Salmon process is currently used for testing and validation only
- 4a. Execute Quality Control on FASTQ Data (
rnaseq-rsem-<PI_NAME>.nf) - 4b. Align FASTQ data to the Worm Genome
- 4c. Quantify the Gene Expression
- 4d. Summarize results for further analysis
- 4e. Aggregate the QC Reports for simplified review
- 5a. Execute DEBrowser to perform Differential Expression Analysis (
utility/start_debrowser.sh) - 5b. Trim Data as needed
- 5c. Produce heatmap visualizations
- 6a. Execute Wormcat Batch (
wormcat_batch.nf)
Note: when running use nextflow run PIPLINE.nf -bg -N [email protected], which will run in the background and email when the process terminates (success or failure)
- MD5 Checksum Report
- FAST QC Reports
- Multi QC Report
- Isoform Quantification
- Gene Quantification
- DESeq2 heatmap visualizations
- Wormcat annotations and visualization of gene set enrichment data
