Predicting Species Accumulation Curves
BBC estimator
CS estimator
Dickens' vocabulary
RFA estimator with bootstrap
RFA estimator
Parameter alpha in the logseries estimator
Logseries estimator
Fisher's butterfly data
Fraction of -mers observed at least times with bootstrap
Fraction of -mers observed at least times
Interpolation
Sampling
Optimal amount of sequencing for scWGS
Predicting -species accumulation curves
Best practice for -SAC
Best practice for -SAC -- a fast version
Predicting -SAC in WES/WGS
Predicting generalized sample coverage with bootstrap
Predicting generalized sample coverage
Simulation
Fitting a zero-truncated negative binomial distribution
Shakespeare's word type frequencies
-mer counts of a metagenomic data
Coverage histogram of a WES data
Read counts of a WES data
Coverage histogram of a WES data
Read counts of a WES data
Coverage histogram of a scWGS data
Coverage histogram of a scWGS data
Social network
Fisher's butterfly data
ZTNB estimator
ZTP estimator
Originally as an R version of Preseq <doi:10.1038/nmeth.2375>, the package has extended its functionality to predict the r-species accumulation curve (r-SAC), which is the number of species represented at least r times as a function of the sampling effort. When r = 1, the curve is known as the species accumulation curve, or the library complexity curve in high-throughput genomic sequencing. The package includes both parametric and nonparametric methods, as described by Deng C, et al. (2018) <arXiv:1607.02804v3>.