Description Usage Arguments Details Value
Estimate the complexity of a library or sample based on unique fragments using Daley and Smith's implementation of Good-Toulmin rational function approximation to solve the missing species problem.
1 |
xx |
The fragments or sample of fragments |
withCI |
Have preseq compute 95 percent confidence intervals for plots? |
... |
Other arguments to pass on to preseqR |
Original functions in preseqR v2.0.1.1 for this were: preseqR.rfa.curve and preseqR.rfa.species.accum.curve
The new functions as of the version 3.1.2 are:
ds.mincount == preseqR.rfa.curve ds.mincount.bootstrap == preseqR.rfa.species.accum.curve
The new functions return generators that can have data passed to them instead of returning a data frame as in version 2.0.1.1.
It is worth noting that these functions return *non-bootstrapped* fragment estimates but uses the bootstrapped variance estimates to calculate CI. This is a function of the latest implementation of preseqR.
A data frame with results
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