Overview

This repository provides a complete pipeline for assembling and analyzing the genome of SARS-CoV-2 using Illumina paired-end sequencing data. It includes steps for quality control, mapping, variant calling, primer clipping, consensus sequence generation, lineage annotation, and phylogenetic analysis.

Key Features

• Automated environment setup using mamba and conda
• Comprehensive quality control with fastqc and fastp
• Mapping and visualization using minimap2, samtools, and IGV
• Primer sequence clipping for clean alignments
• Variant calling with freebayes and VCF filtering with vcfR
• Consensus sequence generation and lineage assignment with pangolin
• Phylogenetic analysis and multiple sequence alignment with mafft and iqtree
• Clear documentation and modular structure

System Requirements

• Operating System: Linux (tested on Fedora 38)
• Processor: Intel i5 or equivalent, with multithreading support
• Memory: Minimum 8 GB
• Software: Anaconda/Miniconda, mamba, R, and the listed bioinformatics tools

Dependencies

The pipeline requires the following tools, managed via mamba:

• QC: fastqc, fastp, multiqc
• Mapping: minimap2, samtools, bamclipper
• Variant Calling: freebayes, vcftools, bcftools
• Sequence Analysis: vcfR, mafft, iqtree, pangolin
• Visualization: gnuplot, IGV, jalview

Installation

1. Clone the repository:

   git clone https://github.com/<username>/sars2-genome-assembly.git
   cd sars2-genome-assembly

2. Install mamba and create the environment:

   wget "https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-Linux-x86_64.sh"
   bash Mambaforge-Linux-x86_64.sh
   conda update -y conda
   mamba env create -p ./envs/projectSARS --file environment.yaml
   mamba activate ./envs/projectSARS

Pipeline Workflow

1. Environment Setup: Install dependencies and configure the environment.
2. Data Preparation: Download input datasets and reference genomes.
3. Quality Control: Evaluate and preprocess raw sequencing reads.
4. Mapping: Align reads to the reference genome.
5. Primer Clipping: Remove primer sequences from alignments.
6. Variant Calling: Identify variants in the genome.
7. Filtering & Masking: Use an R script for QC and filtering of VCF files.
8. Consensus Generation: Generate consensus sequences from filtered variants.
9. Lineage Annotation: Assign SARS-CoV-2 lineages using pangolin.
10. Phylogenetic Analysis: Perform multiple sequence alignment and build phylogenetic trees.

Input Data

• Illumina paired-end sequencing data
• SARS-CoV-2 reference genome (NCBI accession: NC_045512.2)

Output

• Quality control reports (.html, .json)
• Aligned sequences in BAM and VCF formats
• Consensus sequences in FASTA format
• Lineage annotations
• Phylogenetic trees and visualizations

Usage

1. Edit the config.sh file to specify input data paths and parameters.
2. Run the pipeline:

   bash scripts/run_pipeline.sh

3. View results in the results/ directory.

References

This pipeline builds on the work of numerous bioinformatics tools and methodologies. Key references include:

• Heng Li, Minimap2: pairwise alignment for nucleotide sequences, Bioinformatics, 2018
• Petr Danecek, James K Bonfield, et al., SAMtools and BCFtools, GigaScience, 2021
• Áine O'Toole, Anthony Underwood, et al., Pangolin tool, Virus Evolution, 2021
• Katoh, K., & Standley, D. M., MAFFT multiple sequence alignment software, Molecular Biology and Evolution, 2013

Acknowledgments

This project was developed as part of the SARS-2 Bioinformatics & Data Science course by the Freie Universität Berlin and the Robert Koch Institute. Special thanks to Max von Kleist and Martin Hölzer for their guidance.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For questions or issues, please contact:

• Abhinav Mishra
• Email: mishraabhinav36@gmail.com

Data & File description

References

1. bamstats.pl script, 2012-2014 Genome Research Ltd (Author: Petr Danecek pd3@sanger.ac.uk)
2. Anon, 2020. Anaconda Software Distribution, Anaconda Inc. Available at: https://docs.anaconda.com/.
3. Philip Ewels, Måns Magnusson, Sverker Lundin, Max Käller, MultiQC: summarize analysis results for multiple tools and samples in a single report, Bioinformatics, Volume 32, Issue 19, October 2016, Pages 3047–3048, https://doi.org/10.1093/bioinformatics/btw354
4. Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online].
5. Shifu Chen, Yanqing Zhou, Yaru Chen, Jia Gu, fastp: an ultra-fast all-in-one FASTQ preprocessor, Bioinformatics, Volume 34, Issue 17, September 2018, Pages i884–i890, https://doi.org/10.1093/bioinformatics/bty560
6. Heng Li, Minimap2: pairwise alignment for nucleotide sequences, Bioinformatics, Volume 34, Issue 18, September 2018, Pages 3094–3100, https://doi.org/10.1093/bioinformatics/bty191
7. Petr Danecek, James K Bonfield, Jennifer Liddle, John Marshall, Valeriu Ohan, Martin O Pollard, Andrew Whitwham, Thomas Keane, Shane A McCarthy, Robert M Davies, Heng Li, Twelve years of SAMtools and BCFtools, GigaScience, Volume 10, Issue 2, February 2021, giab008, https://doi.org/10.1093/gigascience/giab008
8. Robinson, J. T., Thorvaldsdóttir, H., Winckler, W., Guttman, M., Lander, E. S., Getz, G., & Mesirov, J. P. (2011). Integrative genomics viewer. Nature biotechnology, 29(1), 24–26. https://doi.org/10.1038/nbt.1754
9. O'Toole Á, Hill V, Pybus OG et al. Tracking the international spread of SARS-CoV-2 lineages B.1.1.7 and B.1.351/501Y-V2 [version 1; peer review: 3 approved]. Wellcome Open Res 2021, 6:121 (https://doi.org/10.12688/wellcomeopenres.16661.1)
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11. Rambaut, A., Holmes, E.C., O’Toole, Á. et al. A dynamic nomenclature proposal for SARS-CoV-2 lineages to assist genomic epidemiology. Nat Microbiol 5, 1403–1407 (2020). https://doi.org/10.1038/s41564-020-0770-5
12. Tool for QC with consensus sequences https://github.com/rki-mf1/president
13. Au, C., Ho, D., Kwong, A. et al. BAMClipper: removing primers from alignments to minimize false-negative mutations in amplicon next-generation sequencing. Sci Rep 7, 1567 (2017). https://doi.org/10.1038/s41598-017-01703-6
14. Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. arXiv preprint arXiv:1207.3907 [q-bio.GN] 2012
15. Vcflib and tools for processing the VCF variant call format. Erik Garrison, Zev N. Kronenberg, Eric T. Dawson, Brent S. Pedersen, Pjotr Prins. bioRxiv 2021.05.21.445151; doi: https://doi.org/10.1101/2021.05.21.445151
16. Petr Danecek, Adam Auton, Goncalo Abecasis, Cornelis A. Albers, Eric Banks, Mark A. DePristo, Robert E. Handsaker, Gerton Lunter, Gabor T. Marth, Stephen T. Sherry, Gilean McVean, Richard Durbin, 1000 Genomes Project Analysis Group, The variant call format and VCFtools, Bioinformatics, Volume 27, Issue 15, August 2011, Pages 2156–2158, https://doi.org/10.1093/bioinformatics/btr330
17. Waterhouse, A.M., Procter, J.B., Martin, D.M.A, Clamp, M., Barton, G.J (2009), "Jalview version 2: A Multiple Sequence Alignment and Analysis Workbench,” Bioinformatics 25 (9) 1189-1191 doi: 10.1093/bioinformatics/btp033
18. Nguyen, L. T., Schmidt, H. A., von Haeseler, A., & Minh, B. Q. (2015). IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Molecular biology and evolution, 32(1), 268–274. https://doi.org/10.1093/molbev/msu300
19. Bui Quang Minh, Heiko A Schmidt, Olga Chernomor, Dominik Schrempf, Michael D Woodhams, Arndt von Haeseler, Robert Lanfear, IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era, Molecular Biology and Evolution, Volume 37, Issue 5, May 2020, Pages 1530–1534, https://doi.org/10.1093/molbev/msaa015
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Device Info

The analysis and results was done and generated on

OS Fedora Linux 38
Kernel Linux 6.4.15-200.fc38.x86_64
Processor Intel i5-8250U (8 slots), with CUDA support
Graphics UHD 620 (KBL GT2)
Memory 8 GB

SARS-CoV-2 genome assembly from Illumina reads

Course: SARS-2 Bioinformatics & Data Science
Intructors: Max von Kleist, Martin Hölzer
Institution: Freie Universität Berlin, Robert-Koch Institute