SNP_pipeline.ipynb contains following steps:

1. Installing dependencies

This step will install all software used in this pipeline, assuming python and conda/anaconda already installed ​

2. Dictionary of necessary files

SRA files and sample names can be stored in a dictionary, which also may be used for accessing files. SRA numbers for samples of the interest can be obtained from NCBI (https://www.ncbi.nlm.nih.gov/sra) ​

3. Getting SRA data

Creating subfolders for SRA files and downloading them using sra-tools ​

4. Quality trimming with Trimmomatic

Quality trimming and removing primers and adapters (if there are any)

• Input files - reads 1 and 2
• Output files - paired and unpaired reads.
  ​ Since in this pipeline only paired reads used, optionally input files and unpired output files can be removed to save some space on drive.
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5. Running FastQC with trimmed and paired files

Quality of trimmed and paired files can be checked using FastQC

• Input files - trimmed and paired reads
• Output files - evaluation files, produced by FastQC ​

6. BWA alignment and SNP calling

In this step, it is neceessary:

1. Provide reference sequences for each of the samples
2. bwa alignment - align reads to reference sequence
   • Input files - paired and trimmed reads
   • Output files - aligned files in filename.sam format
3. Convert sam files into bam files
   • Input files - sam files
   • Output files - bam files
4. Sort and index bam files
   • Input files - bam files
   • Output files - sorted and indexed bam files
5. Performing SNP calling using Freebayes
   • Input files - reference and sorted bam files
   • Output files - vcf files with SNP observed
6. If necessary, use vcftools for filtering ​

7. SNP ratio

Calculating and extracting the ratio between different variants in called SNPs. If in some of the SNPs one of the variants presented in more than 90% of the reads it will be filtered out during this step (can be easily changed or removed) ​

8. SNP for all nematodes, table and barplot

Create barplot for samples of the interest by species and gene regions

• Output files - figure with barplots, indicating the amount of SNP per 50 bp, by species, genes and isolates ​

9. SNP heatmapes by species and genes separately

Create heatmaps for species, presented by several isolates to see variability of SNPs within species

• Output files - heatmaps-like figures with SNP positions by genes (regions) and different isolates within species