snippy VS awesome-CRISPR

This should be of help, if you think you can get have a decent (closely related) reference genome from NCBI: https://github.com/tseemann/snippy

snippy is a nice tool for this!

So, let's say I have a batch of 20 samples, and I found evidence for my genus of interest in 5. What I've done is used Snippy (https://github.com/tseemann/snippy) with mapping based on a reference species in the genus. Snippy finds shared "core" regions of the reference species that are present in all samples and compares the SNPs between the samples. I find that each sample has distinct SNPs, which I believe indicates that the bacteria in each sample are not the same isolate. Thus, I am trying to argue that the bacteria could not have come from a shared contamination event during library prep. Does this make things more clear?

My first idea was to assemble the contigs into scaffolds (e. g. using RagTag) and then look for a tool that can identify these mutations. However, I've also come across snippy, which is a tool that can identify mutations from reads. I don't know if I can just apply it to contigs though (probably not).

I would use snippy for this if there references are haploid genomes https://github.com/tseemann/snippy

[18:37:12] Obtained from https://github.com/tseemann/snippy

That's helpful to know, actually. I recommend looking through the abundant tools for analysis of CRISPR experiments. I would guess someone out there has a tool for assessing cut efficacy from NGS/amplicon reads. https://github.com/davidliwei/awesome-CRISPR is a good place to start, and if you don't find what you need, make your own and publish it. ;)

Is it mostly only for programming/software lists? A couple I searched for like this one: https://github.com/davidliwei/awesome-CRISPR wasn't showing up, but it's obviously more biology/software based.