Coverage
The coverage calculator returns Good’s coverage for an OTU definition. This calculator can be used in the summary.single, collect.single, and rarefaction.single commands.
\[C=1-\frac{n_1}{N}\]where,
\(n_{1}\) = the number of OTUs that have been sampled once
\(N\) = the total number of individuals in the 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 third column indicates the number of OTUs with only one indivdiual, the fourth the number of OTUs with two individuals, etc. Good’s coverage is then calculated using the values found in the subsequent columns. For demonstration we will calculate Good’s coverage for an OTU definition of 0.03:
\[C=1-\frac{75}{98} = 0.23\]Running...
mothur > summary.single(calc=coverage)
...and opening 98_lt_phylip_amazon.fn.summary gives:
label coverage
unique 0.040816
0.00 0.061224
0.01 0.102041
0.02 0.142857
0.03 0.234694 <---
0.04 0.295918
0.05 0.438776
0.06 0.510204
0.07 0.551020
0.08 0.642857
0.09 0.642857
0.10 0.653061
These are the same values that we found above for a cutoff of 0.03.