Normalisation of features

I am having problem with normalisation of data. I am new in bioinformatics. Why it is necessary. Where should I start task in qiime2.

Read the literature. Here is a good place to start:

Check out the QIIME 2 tutorials. Normalization steps are described and explained at the appropriate steps. Any QIIME 2 commands that require normalization have that normalization built in. So rarefying is used prior to alpha/beta diversity (as part of the core-metrics pipelines), and ANCOM (for differential abundance testing) uses its own normalization. But the short answer: normalization occurs after you have a feature table, but before you are attempting to perform any type of direct comparison between samples (since things like sequence depth are variable between samples but do not relate to biomass so must be normalized prior to statistical comparisons)


I had similar question about normalisation of data in feature table. I would like to know what are current normalisation strategies built in qiime2 2019.4 version.

Take a look at the qiime diversity core-metrics-phylogenetic plug-in in this tutorial

You will notice that this plug-in includes this setting --p-sampling-depth 1103, which will normalize by randomly subsampling to an even depth of 1103 reads per sample.

Does that help answer your question? You might find other good information in that tutorial too!

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Thank you so much Collin. Really your answer help me a lot.

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