SARS_CoV19_INHOUSE

Pipeline is used to process SARS-CoV19 WGS data.

Workflow summary

1. The analysis begins with quality control of raw fastq files:
   • Adapter sequences are removed using cutadapt[1] (screening for default illumina adapter sequences)
   • Reads are trimmed based on base quality (Phred score >= 30) and length (read length >= 50bp) using fastp[2]
2. Reads that passed QC are aligned to the reference using bwa[3].
   • The output from bwa[3] is passed to samtools[6] to produce binary alignment map (bam) file.
3. Primer sequences are removed from bam file using ivar[4].
   • Primer sequences should be provided in Browser Extensible Data (bed) format - generated from fasta file using bwa[3] & bedtools[5].
4. To improve alignment quality, local realignment is performed on primer-free bam file using abra[9].
   • bed file with realignment targets is created from primer-free bam file using bedtools[5].
5. Alignment QC metrics are extracted from raw and primer-free bam files using samtools[6].
6. Variant-calling is performed on post-realignment bam file using freebayes[7].
7. Raw variants are filtered using vcflib/vcffilter[10] based on quality (QUAL > 30) and sequencing depth (DP > 15).
8. Filtered variants are annotated using snpEff[8], using genbank reference.
9. Consensus sequence is generated (in fasta format) from post-realignment bam file using ivar[4].
   • invalid base (N) is called if coverage is less that 15.
10. Sample id is added to fasta header and invalid bases are replaced with N using bash scripts.
11. Annotated vcf file is converted to csv format and coverage depth plot is generated from sequencing depth data using inhouse-developed python scripts.
12. Temporary files are deleted after each sample is processed.
13. Lineage assignment is performed based on consensus sequence using Pangolin[11].
14. Inhouse-developed python & bash scripts are used to control the flow of analysis for multiple samples, generate summary report and visualize the results.

Tools & References

1. cutadapt 2.31 - https://doi.org/10.14806/ej.17.1.200
2. fastp 0.20.1 - https://doi.org/10.1093/bioinformatics/bty560
3. bwa 0.7.17-r1198-dirty - https://arxiv.org/abs/1303.3997
4. ivar 1.3.1 - https://doi.org/10.1186/s13059-018-1618-7
5. bedtools v.2.30.00 - https://doi.org/10.1093/bioinformatics/btq033
6. samtools 1.12 - https://doi.org/10.1093/bioinformatics/btp352
7. freebayes v0.9.21 - https://arxiv.org/abs/1207.3907
8. snpEff 5.0e - https://pcingola.github.io/SnpEff/adds/SnpEff_paper.pdf
9. abra 0.97 - https://doi.org/10.1093/bioinformatics/btu376
10. vcflib 1.0.2 - https://doi.org/10.1101/2021.05.21.445151
11. Pangolin - https://doi.org/10.1038/s41564-020-0770-5