RNASEQ-QC is a quality control analysis pipeline for RNA sequencing data obtained from an organism with an available reference genome and annotation.

STAGES:

- preprocessing: 
    - fastp : Read filtering 
    - FASTQC : Read QC
    - SortMeRNA : ribosomal RNA quantification
    - bowtie2 : globin quantification

- processing:
    - STAR : alignment to the reference genome 
    - salmon: quantification
    - RSeQC : quality control 

- postprocessing:
    - R : additional qc
    - multiqc : regroup all qc

QUICK START:

1. Prepare input files:

   Metadata Requirements: The metadata file should include the following mandatory column: SampleID: should contain the name of the fastq file for each sample SampleName: refer to the name of the sample as you want it to appear in the figures Group: needed to color samples belonging to same group Run_Name: a new output directory will be created based on run name
   Experiment_Name: an additional new output subdirectory will be created based on experiment name Include: Specify 'Y' to include the sample in the analysis or 'N' to exclude it. Path: relative path that specifies the location of the fastq raw file relative to the current working directory

   Reference Genome and annotation files:

   • Download from your favorite database: gtf, bed transcript files
   • Generate mapping indexes with STAR (STAR --runMode genomeGenerate --runThreadN 25 --genomeDir [OUTPUT_DIRECTORY] --genomeFastaFiles [FASTA_FILE] --sjdbGTFfile [GTF8FILE] --sjdbOverhang 74)
   • Generate correspondance file between gene id and gene biotype from gtf file (use get_corresp_geneID_geneBiotype_from_gtf.py provided in script directory)
   • download ribosomal RNA database from https://github.com/sortmerna/sortmerna/tree/master/data/rRNA_databases
   • create index for hemoglobin transcript if your samples are from blood origin

   Config file: Prepare a config file similar to the one provided in the test dataset. The config file mostly contain different paths to the necessary input files.

2. Create conda environement using provided yaml file

   conda env create -n rnaseq-qc -f rnaseq-qc.yaml

   Activate the conda environement

   conda activate rnaseq-qc

   Run the pipeline with command line:

   snakemake --directory test/ --snakefile Snakefile --use-conda --conda-prefix path/to/conda --configfile test/config.json -p