araguram/mutato repository overview

To download:

docker pull araguram/mutato

Before you run mutato:

1. When you submit samples for Sanger sequencing, name them in a way that makes sense, e.g. clone01, clone02, clone03... clone10, etc. It's better to number them with leading zeros as above, instead of clone1, clone2, clone3... clone10, since this will allow the samples to be sorted appropriately. Don't use any underscores in the sample names.
2. This script assumes Quintara's standard file naming convention, where the characters before the first underscore in the .ab1 filename denote the sample name.

To run mutato with Sanger sequencing reads:

1. Create a new folder where you will run mutato. Avoid spaces in the directory names in the entire path to this folder.
2. Move your reference fasta file (reference DNA sequence) to this folder. Make sure the record name in the fasta file (first line starting with >) is the same as the name of the fasta file (excluding the filename extension). In other words, SP14a.fasta should contain one record named SP14a.
3. In the above folder, create a folder named ab1_input.
4. Move all of the *.ab1 sequencing chromatogram files into the ab1_input folder.
5. Make sure that your current working directory contains the ab1_input folder and reference fasta file (should be the directory you created in step 1).
6. Run the following command with your desired parameters:

docker run -v ${PWD}:/DATA -w /DATA -i araguram/mutato run_mutation_analysis.sh -f reference.fasta -s 2 -p 0.8 -t 4 -d 0

To run mutato with Illumina sequencing reads:

1. Create a new folder where you will run mutato.
2. Move your reference fasta file (reference DNA sequence) to this folder. Make sure the record name in the fasta file (first line starting with >) is the same as the name of the fasta file (excluding the filename extension). In other words, SP14a.fasta should contain one record named SP14a.
3. In the above folder, create a folder named fastqs.
4. Move all of the *.fastq.gz files into the fastqs folder (one file per clone).
5. Make sure that your current working directory contains the fastqs folder and reference fasta file (should be the directory you created in step 1).
6. Run the following command with your desired parameters:

docker run -v ${PWD}:/DATA -w /DATA -i araguram/mutato run_mutation_analysis-fastq_input.sh -f reference.fasta -s 2 -p 0.8 -t 4 -d 0

Parameters:

-f reference fasta filename
-s residue number of the first amino acid included in the fasta file (for numbering amino acids appropriately)
-p (optional) p-value below which to call SNPs (default = 0.8)
-t (optional) number of CPU processes (default = 1)
-d (optional) penalize indels in alignment (set to 1 if desired, default = 0)
-q (optional) quality trimming from ends (set to value <= 30 if desired, default = 0, i.e. no trimming)

Notes on reference fasta sequence

Mutato will work best if all of your reads can align fully to the reference fasta sequence. For example, if you have a read near the 5' end of your gene of interest that reads part of the plasmid/phage backbone, you should include that plasmid/phage backbone sequence in your reference fasta file. Make sure the sequence still starts in frame with your gene of interest. You can change the -s flag appropriately, and it can be a negative number.

Notes on penalizing indels in alignment

For libraries with high diversity over a few consecutive positions (e.g. NNK libraries), consider penalizing indels, as the default alignment parameters might incentivize calling these highly diverse positions as indels rather than multiple consecutive SNPs. Setting -d 1 will set the following bwa alignment parameters: -B 3 -O 10 -E 3 (see http://bio-bwa.sourceforge.net/bwa.shtml⁠ for explanations of these parameters).