Hello,

I have a deep sequencing experiment to analyze and I am hesitant about the variant caller algorithm/program to use as I have some doubts concerning scalability

For a small experiment, not a deep-seq one, we usually rely on the gatk recommendations and best practicies guides, by combining a couple of tasks such as deduplication, this makes the analysis time more or less acceptable. For a deep sequencing experiment, there is no rational about removing duplicates, which makes the variant call part very long and relatively not scalable.

I didnt try the gatk variant caller yet on deep-seq data but I guess it will take a lot of time, I was wondering what is the best option to do the variant call on a deep seq data in term of scalability, if anyone has tried that in the past, I would be grateful if he can give some hints on the best way of doing this.

Thanks
For 90x coverage, GATK works fine for us. You can parallelize GATK by running it per chromosome. If you want to go even further, freebayes can be safely parallelized to non-overlapping regions of chromosomes. In any case, for most callers, 90x shouldn't be too bad. Do make sure that any high-depth filters that are inherent in the defaults are either turned off or set to more sane numbers for your data.