jwdebelius
May 11, 2019, 9:32pm
2
Hi @m_max ,
Welcome!
There's been a fair bit of discussion around rarefaction here (or maybe Im just involved in a lot of them). It's maybe good to go look into those threads since they'll give you a wide variety of view points. Here are a few to start that I found pretty quickly.
Dear All,
Ive executed QIIME2 analysis for my four different group. Each group consists of unequal sample size.
Group A: 11
Group B: 9
Group C: 31
Group D: 12
and the sequence counts of each sample varies from 182,014 to 4,194.
And I got more abundance in Group C for most of the taxa.
In which way I can normalize the samples and get the abundance of taxa?
Should I do any FPKM/RPKM or log2 normalization method ?
Is there any R or some other tools to normalize OTU abundance.
Hi @Alfred.Burian ,
Thanks for bringing this up!
Without wading too far into this debate, I will point out that rarefying is not always inadmissible , particularly for unweighted UniFrac and other beta diversity methods based on presence/absence of features. This is actually also shown in Fig 4 of the article that you posted, though for other distance methods other normalization strategies perform better.
Second, what you describe is the qiime diversity core-metrics-phylogenetic method, which r…
What would you make of a dataset that, when you run said OTU table through Vegan to calculate distances using defaults (Method==Bray, Binary = FALSE) and depending on whether you filter based on per-sample ASV abundances, you get very different pictures?
For example:
Data is processed with Cutadapt and DADA2 defaults, then...
Situation-1. incorporate all reads of any abundance > 1
Situation-2. Require per-sample ASVs abundance > 100
Now calculate distances, and run metaMDS...
The distances…
In general, would it be advisable to filter by group if your dataset contains multiple sample types?
For example, when working with data from one sample type, I typically filter features that are not found in >95% of samples. I’d like to do this same type of filtering but the dataset I’m working with now is a composite from multiple body sites and environmental samples. All were run on the same lane, so I know that cross-talk might be a problem, and I can handle that by filtering features that …
Hi Nick !
I disagree with the use of a rarefied table for alpha diversity estimation. Is there a better explanation why one should use a rarefied table for alpha-diversity estimates?
Hi Qiime community,
I am preparing to run the alpha and beta diversity metrics on my 16S V4 dataset but had a couple questions about the set up to answer the questions of my study. My study consists of sampling bacteria populations in lake water samples across 3 lakes and from 3 size fractions per lake ( whole water, >20um and <20um). Each lake was sampled once a week for several months.
First I would like to look at how the diversity of the bacteria populations vary between lakes and between…
Best,
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