CHM13 VS kraken2

2) Use bowtie2 to align reads against CHM13. This will let you separate human from nonhuman (important, as human sequences are a common contaminant in many nonhuman genomes).

Code https://github.com/marbl/CHM13

Liftover files are already available from https://github.com/marbl/CHM13

If you’re serious, you can download the current fasta file from this page.

I have created a simulated karyogram based on REPAVER visualisations of the Telomere-to-telomere Consortium's CHM13 assembly:

3) Use Kraken2 to classify remaining reads. I'd start with the standard database.

See more information in: kraken2 manual

If you've got a fast solid state drive with >200G of space, then kraken2 + bracken works really well. First, use kraken2 to map reads to taxa in memory-mapped mode (to reduce system memory consumption):

Yes, that can be done. Bacterial proportions is pretty much what programs like Kraken2 and Centrifuge do.

Or Kraken2

For bacterial metagenomic stuff you can quickly reduce the amount of sequences you need to BLAST by using Kraken2.

While implementing and scaling data analysis pipelines at a biotech startup, I spent most of my time getting new tools running efficiently and scaling them. Implementing something like Kraken2 for genomic analysis (https://github.com/DerrickWood/kraken2) on our infrastructure took weeks and was hard to scale. I expected a library for running these tools on managed infrastructure via an API to exist – like Twilio for sending text messages or Stripe for processing payments – but I couldn't find any.

Toolchest is an API for running data analysis tools easily (i.e. copy and paste a few lines of code), without managing the infrastructure. We're starting with computational genomics tools, but tools in other spaces can be added. Please drop me a message if you have a use case in mind! For example, I've thought about making hashcat powered by Tesla V100 GPUs accessible via our API.

All feedback is welcome! If you're curious about how it works, feel free to check out our docs: https://toolchest-python-client.readthedocs.io/en/latest/use...