I found difficult to intrepret the result. what is the actual meaning of sequencing depth?. Instead of number of otu sequence, sequencing depth was there.
Could you please tell me how to intrepet observed_otu, faith and shannon diversityboxplot?
Based on the alpha rarefaction you should decide, at which depth you want to estimate alpha/beta diversity metrics. In the moving pictures tutorial, it is performed after core metrics, and I am wondering, why. First, you are performing alpha rarefaction with a depth, which is approximately half of your max depth in your table, than you can check, at which depth you can catch rare taxa but at the same time will also preserve the maximum amount of samples.
When you decided, you can calculate all metrics as described in the tutorial https://docs.qiime2.org/2019.10/tutorials/moving-pictures/#alpha-and-beta-diversity-analysis
Or apply it by using next plugins https://docs.qiime2.org/2019.10/plugins/available/diversity/
I have done core metrics analysis after that only I performed alpharefraction analysis. I found difficult to intrepret the graph. As far as I know ,sequecing depth is the point where seqeuence will be level off. In many papers, I saw no of OTU sequence in alpha refraction graph x axis. In my graph why sequencing depth was there?. I want to see otu richness in all of my samples. what plugin or command shoud I follow?
I have done that qiime diversity alpha-group-significance analysis for my sample. I checked whether ulcersize, age , diagonsis making any changes or differences. I have attached my metafile data also for your reference.
could I consider evenness-group-signifcance is statiscally significant ? P value is less than 0.05 in eveness-group-signifcance result where as p value is not good in faith-pd-significance result.
How to intrepret this kind of result? evenness-group-significance.qzv (320.3 KB) faith-pd-group-significance.qzv (320.6 KB) samplemetadata.tsv (562 Bytes)
Dear Asha1
I think I understood what you are asking about.
The problem with your dataset is that you don't have a lot of repeats. You can not compare directly different samples, to test it statistically, it is better to have at least 3 (but 5 and more better) samples that are grouped in one category, and have all the same parameters in metadata file, except of sample-id. It is why you are not getting the graph as you want.
Still, you can obtain a observed_otus-significance.qzv file the same way you got evenness-group-significance.qzv file, open it as an archive or extract with corresponding qiime2 command to obtain a metadata.tsv file from .qzv
From this file you can plot a barplot with samples and alpha-diversity metric as axes in excel or using programming language. But you will not have repeats for this data.
You can't compare different samples directly, you need to compare groups of the samples. It is why you can not compare 'age' - you don't have repeats and data is unique for this category.
For the rest of the columns:
Sex Diagnosis Size of the ucler
Evenness: yes yes no
Faith PD: no no no
