How should I normalize a dataset for non-normally distributed, zero-inflated, and unequal library size?
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7 months ago
seda ▴ 10

Hi everyone!

I have taxonomic abundance count data obtained from shotgun metagenome analysis. My data is not normally distributed and zero-inflated. Each of the samples in my dataset has unequal library size. In this case, how can I normalize my dataset to do all downstream analysis? Let's say, ones I normalize the data, can I use it for all downstream analysis? what i mean is, does each different analysis need a different normalization method?

I am open to any tips/ suggestions and information.

Thank you all!

unequal zero-inflated downstream-analysis library metagenome normalization • 863 views
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You don't need normalization. You need to accurately model your data. That's it.

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could you explain more how I can model my data?

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That's can sadly solve only a semester course in regression modelling :( better several years of stats ofc

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time to open the stats notes :D thanks anyway!

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7 months ago

You should probably be handling your data as compositional. See for example: Microbiome Datasets Are Compositional: And This Is Not Optional.
The reference on the topic is the book Statistical analysis of compositional data by John Aitchison (and the original article) and a more recent view can be found in Aitchison’s Compositional Data Analysis 40 Years On: A Reappraisal

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