This repository contains a Bash script for a variant calling pipeline using tools such as FastQC, MultiQC, BWA, GATK, VEP, and ANNOVAR. The pipeline processes raw paired-end FASTQ files to identify variants and annotate them.

The variant calling pipeline consists of the following steps:

1. Quality control with FastQC: Performs quality control analysis on raw FASTQ files.
2. Aggregate reports with MultiQC: Aggregates FastQC reports into a single, comprehensive report.
3. Align reads to the reference genome with BWA: Aligns paired-end reads to the reference genome using BWA.
4. Convert SAM to BAM, sort, and index with GATK: Converts the SAM file to BAM format, sorts it, and creates an index using GATK.
5. Mark duplicates with GATK: Identifies and marks duplicate reads in the BAM file.
6. Variant calling with GATK HaplotypeCaller: Calls variants from the aligned reads using GATK.
7. Annotate variants with VEP: Annotates variants with VEP (Variant Effect Predictor).
8. Further annotation with ANNOVAR (optional): Optionally annotates variants with ANNOVAR.

• Performs quality control (QC) analysis on raw sequencing data using FastQC and MultiQC.

• Aligns sequencing reads to the reference genome using BWA.

• Preprocesses aligned reads, including sorting, deduplication, and quality filtering.

• Calls variants using GATK HaplotypeCaller.

• Annotates variants using VEP (Variant Effect Predictor) and ANNOVAR.

To use the pipeline, follow these steps:

1. Set Up Environment:

   • Ensure that the necessary tools (FastQC, MultiQC, BWA, GATK, VEP, and ANNOVAR) are installed and accessible in your environment.
   • Set the paths to the reference genome, input FASTQ files, BWA index, GATK bundle, and output directory in the script.

2. Run the Pipeline:

   • Execute the provided Bash script (variant_calling.sh) in your terminal or command prompt.
   • Monitor the progress of the pipeline and check for any error messages.

3. Review Output:

   • After the pipeline completes successfully, review the output files generated in the specified output directory.

• This pipeline assumes that the required tools are installed and accessible in your environment. Adjustments may be necessary based on your specific setup.
• Modify the script and parameters as needed to adapt to different reference genomes, sample names, or analysis requirements.
• Ensure that input FASTQ files are properly formatted and that paths to all required files and directories are correctly specified.

• Rugved Rane

This project is licensed under the MIT License.

1. FastQC:

   • Citation:
     • "FastQC: A quality control tool for high throughput sequence data."
     • Simon Andrews. 2010.
     • https://www.bioinformatics.babraham.ac.uk/projects/fastqc/

2. MultiQC:

   • Citation:
     • "MultiQC: Summarize analysis results for multiple tools and samples in a single report."
     • Philip Ewels, Måns Magnusson, Sverker Lundin, and Max Käller.
     • Bioinformatics, Volume 32, Issue 19, 1 October 2016, Pages 3047–3048.
     • https://academic.oup.com/bioinformatics/article/32/19/3047/2196506

3. BWA (Burrows-Wheeler Aligner):

   • Citation:
     • "Fast and accurate short read alignment with Burrows-Wheeler Transform."
     • Heng Li and Richard Durbin.
     • Bioinformatics, Volume 25, Issue 14, 15 July 2009, Pages 1754–1760.
     • http://bio-bwa.sourceforge.net/

4. GATK (Genome Analysis Toolkit):

   • Citation:
     • "The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data."
     • McKenna A, Hanna M, Banks E, et al.
     • Genome Research, Volume 20, Issue 9, September 2010, Pages 1297-1303.
     • https://gatk.broadinstitute.org/

5. VEP (Variant Effect Predictor):

   • Citation:
     • "Ensembl variant effect predictor."
     • McLaren W, Gil L, Hunt SE, et al.
     • Bioinformatics, Volume 26, Issue 16, 15 August 2010, Pages 2069–2070.
     • https://www.ensembl.org/info/docs/tools/vep/index.html

6. ANNOVAR:

   • Citation:
     • "ANNOVAR: Functional annotation of genetic variants from high-throughput sequencing data."
     • Wang K, Li M, Hakonarson H.
     • Nucleic Acids Research, Volume 38, Issue 16, 1 August 2010, Page e164.
     • https://annovar.openbioinformatics.org/en/latest/