Shen
The shen calculator returns the Shen estimate of the number of additional OTUs that would be observed for an additional level of sampling. This calculator can be used in the summary.single, collect.single, and rarefaction.single commands; however, it really only makes sense to use it with the summary.single command.
\[S_{additional}=f_0\left[1-\left(1-\frac{f_1}{nf_0}\right)^m\right]\]where,
\(f_0\) = the number OTUs that were observed 0 times; this is estimated as the result of the ACE estimator minus S~obs~
\(f_1\) = the number OTUs that were observed 1 times
\(N\) = the total number of individuals in the sample
\(M\) = the number of additional individuals to sample
Open the file 98_lt_phylip_amazon.fn.sabund generated using the Amazonian dataset with the following commands:
mothur > read.dist(phylip=98_lt_phylip_amazon.dist, cutoff=0.10)
mothur > cluster()
The 98_lt_phylip_amazon.fn.sabund file is also outputted to the terminal window when the cluster() command is executed:
unique 2 94 2
0.00 2 92 3
0.01 2 88 5
0.02 4 84 2 2 1
0.03 4 75 6 1 2
0.04 4 69 9 1 2
0.05 4 55 13 3 2
0.06 4 48 14 2 4
0.07 4 44 16 2 4
0.08 7 35 17 3 2 1 0 1
0.09 7 35 14 3 3 0 0 2
0.10 7 34 13 3 2 0 0 3
The first column is the label for the OTU definition and the second column is an integer indicating the number of sequences in the dominant OTU. The Shen estimator is then calculated using the values found in the subsequent columns. For demonstration we will calculate the Shen estimator for an OTU definition of 0.03. Using the ACE estimator, the estimated richness for a cutoff of 0.03 is 543.7. Thus, since there are 84 observed OTUs there are 459.7 unobserved OTUs. We can then predict the number of additional OTUs that would be sampled after sampling 50 additional individuals:
\[S_{additional}=S_{additional}= 459.7\left[1-\left(1-\frac{75}{98\left(459.7\right)}\right)^{50}\right]=36.7\]mothur > summary.single(calc=shen, size=50)
...and opening 98_lt_phylip_amazon.fn.summary gives:
label shen
unique 47.462990
0.00 46.205222
0.01 43.711943
0.02 42.380741
0.03 36.745312 <---
0.04 33.133013
0.05 25.007797
0.06 21.406017
0.07 19.106443
0.08 15.681580
0.09 16.097046
0.10 16.628777
These are the same values that we found above for a cutoff of 0.03. You can change the size parameter as long as it stays as small or smaller than the number of individuals you have already sampled. The default for the size option is the number of sequences that have already been sampled.