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Assigning taxonomy to shotgun metagenomic reads: sequence alignment or composition?

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  • fanli
    replied
    A recent analysis of HMP data used a k-mer approach (LMAT) to remove additional human variation:
    http://genome.cshlp.org/content/25/7/1056.full

    Leave a comment:


  • Assigning taxonomy to shotgun metagenomic reads: sequence alignment or composition?

    I'm interested in identifying bacterial pathogens from shotgun metagenomic data. Crudely, I envisage the pipeline to be something like this:
    1) QC reads
    2) Filter out human sequences
    3) Identify pathogen sequences

    Typically it seems people use the following types of tools for the corresponding steps above:
    1) Trimmomatic/cut-adapt
    2) Bowtie2/SNAP/BWA against human reference genome(s)
    3) Bowtie2/SNAP/BWA against reference bacterial genomes database

    My question is can steps 2) and/or 3) be replaced with a sequence composition based approach? (E.g. a k-mer method, such as Kraken, LMAT or CLARK)

    Of course k-mer methods will be faster but less sensitive than read alignment with a tool like Bowtie2. Additionally, read alignment uses paired-read and quality score info that k-mer approaches don't use. However, there seems to be an increasing trend to adopt 'alignment-free' or 'psudoalignment' approaches and I'm not sure how to evaluate the trade-offs. I'd be grateful for any advice. Thanks.
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