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The dist.shared command will generate a phylip-formatted distance matrix that describes the dissimilarity (1-similarity) among multiple groups. This command will calculate any of the calculators describing the similarity in community membership or structure. This tutorial uses the data files in AbRecovery.zip.

Default settings

To run dist.shared() the read.otu command must first be run with either the list and group option or the shared option. Using the antibiotic recover data do the following:

mothur > read.dist(phylip=abrecovery.dist, cutoff=0.10)
mothur > cluster()
mothur > read.otu(list=abrecovery.fn.list, group=abrecovery.groups, label=0.03)
mothur > dist.shared()

This will generate phylip-formatted lower-triangle distance matrices for the classical Jaccard and Yue & Clayton theta values. The output files are as follows:


B	0.733333	
C	0.846154	0.878049	


B	0.69455	
C	0.953499	0.93937



Using the calc option allows one to select any of the calculators of similarity of community membership and structure. The different calculators can be separated with hyphens (i.e. "-"). For example the following command will generate distance matrices for the Jaccard coefficient using richness estimators, the Yue & Clayton theta, and the Bray-Curtis index:

mothur > dist.shared(calc=jest-thetayc-braycurtis)

Keep in mind that these are distances, which are calculated as one minus the similarity value.


At this point, if you run the following command:

mothur > get.group()

You would have seen that there were 3 groups here: A, B, and C. If you just want the distances between groups A and B, A and C, or B and C enter the following (this is an admittedly silly example):

mothur > dist.shared(groups=A-B)
mothur > dist.shared(groups=A-C)
mothur > dist.shared(groups=B-C)

Keep in mind that these will output to files with the same name. So, it is important to change the file name between commands. The following reverts to the default behavior:

mothur > dist.shared(groups=all)

This is the same as:

mothur > dist.shared(groups=A-B-C)


There may only be a couple of lines in your OTU data that you are interested in summarizing. There are two options. You could: (i) manually delete the lines you aren't interested in from you rabund, sabund, list, or shared file; (ii) or use the label option. If you only want to read in the data for the lines labeled unique, 0.03, 0.05 and 0.10 you would enter:

mothur > dist.shared(label=unique-0.03-0.05-0.10)


The output option allows you specify the form of the matrix generated by dist.shared. By default, dist.shared will generate a phylip formatted lower triangle matrix. If you set output to "square" a phylip formatted square matrix will be generated.

mothur > dist.shared(output=square)