Chapter 3 Beta diversity mapping description

3.1 Upload sample data

You need to upload two data files including sample OTU result file and metadata file.

Such as

Sample Achimill Agrostol Airaprae Alopgeni Anthodor Bellpere Bromhord Chenalbu Cirsarve Comapalu Eleopalu Elymrepe Empenigr Hyporadi Juncarti Juncbufo Lolipere Planlanc Poaprat Poatriv Ranuflam Rumeacet Sagiproc Salirepe Scorautu Trifprat Trifrepe Vicilath Bracruta Callcusp
1 1 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 7 0 4 2 0 0 0 0 0 0 0 0 0 0
2 3 0 0 2 0 3 4 0 0 0 0 4 0 0 0 0 5 0 4 7 0 0 0 0 5 0 5 0 0 0
3 0 4 0 7 0 2 0 0 0 0 0 4 0 0 0 0 6 0 5 6 0 0 0 0 2 0 2 0 2 0
4 0 8 0 2 0 2 3 0 2 0 0 4 0 0 0 0 5 0 4 5 0 0 5 0 2 0 1 0 2 0
5 2 0 0 0 4 2 2 0 0 0 0 4 0 0 0 0 2 5 2 6 0 5 0 0 3 2 2 0 2 0

The first column is the sample id,the other column is the abundance of each indicator in different samples.

Sample group
1 SF
2 BF
3 SF
4 SF
5 HF
6 HF
7 HF
8 HF
9 HF

The first column is the sample id,the second column is the grouping of samples.

Paying attention, please ,you need to upload the file in the format of the sample data.

3.2 Different beta diversity analysis tools

3.2.1 Different drawing tools

3.2.2 PCoA

Dissimilarity index, partial match to “manhattan,” “euclidean,” “canberra,” “clark,” “bray,” “kulczynski,” “jaccard,” “gower,” “altGower,” “morisita,” “horn,” “mountford,” “raup,” “binomial,” “chao,” “cao,” “mahalanobis,” “chisq” or “chord.”

The Jaccard and Bray-curtis dissimilarity coefficients are commonly used in bioinformatics analysis and are the basis for calculating species similarity.

It should be noted that the focus of these two dissimilarity coefficients is different.

In analysis, Jaccard only considers the presence or absence of species in the sample, not the abundance.

The Bray-curtis calculation not only considers the presence or absence of species in the sample, but also considers the relative abundance of different species.

This button can choose whether to perform R-value and P-value calculations on the data. R^2 can quantify the strength of the relationship between the model response variable and the dependent variable. The p-value test can determine how reliable the fitted equation is.

3.2.3 PCA

Whether to add labels to each point

Adjust label position

Adjust label font size

Adjust the aspect ratio of the drawing

3.2.4 NMDS

The function offers different standardization methods for community data:

Dissimilarity index, partial match to “manhattan,” “euclidean,” “canberra,” “clark,” “bray,” “kulczynski,” “jaccard,” “gower,” “altGower,” “morisita,” “horn,” “mountford,” “raup,” “binomial,” “chao,” “cao,” “mahalanobis,” “chisq” or “chord.”It is the same as PCA distance matrix method.