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  • comparative metagenomics

    hi all,

    We are designing a comparative metagenomics experiment where we may run 3 different conditions with several individuals per condition. I am trying to see what would be an appropriate way for analysis and I got down to two ideas.

    On one hand I could pool all reads from the different individuals per condition, to get a "consensus" metagenome per condition. This way, I reduce the analysis down to comparing three metagenomes. I think that pooling the replicates will help me detect low represented organisms, but on the other hand I lose biological variability. This analysis would probably go down the qualitative way.

    On the other hand, I can assemble one metagenome per individual and then compare them between groups taking into account the reps. This analysis would then go down a (semi)quantitative way. But I am not sure how to handle that, what would be the data to compare or how to get the data at all.

    I have seen that MEGAN 2.0 seems to do a nice job on comparing metagenomes, but it seems to be a one vs one approach, more like the first option of analysis.

    See for example:
    Background Metagenomics is a rapidly growing field of research that aims at studying uncultured organisms to understand the true diversity of microbes, their functions, cooperation and evolution, in environments such as soil, water, ancient remains of animals, or the digestive system of animals and humans. The recent development of ultra-high throughput sequencing technologies, which do not require cloning or PCR amplification, and can produce huge numbers of DNA reads at an affordable cost, has boosted the number and scope of metagenomic sequencing projects. Increasingly, there is a need for new ways of comparing multiple metagenomics datasets, and for fast and user-friendly implementations of such approaches. Results This paper introduces a number of new methods for interactively exploring, analyzing and comparing multiple metagenomic datasets, which will be made freely available in a new, comparative version 2.0 of the stand-alone metagenome analysis tool MEGAN. Conclusion There is a great need for powerful and user-friendly tools for comparative analysis of metagenomic data and MEGAN 2.0 will help to fill this gap.

    It would be great if anyone could share ideas, software, references or experience on such an experiment.



  • #2
    It seems to me that it is always better to treat each replicate separately, at least at the stage of library preparation and sequencing. Not being able to describe the biological variability is a real setback in many omics studies, maybe even at the level fo bad experimental design. You can always combine the libraries in the analysis. It does cost more, though.

    BTW, this paper has some interesting ideas on how to look at biological replicates:

    Good luck


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