afufs: Calculate Fu's Fs for arbitrary parameters - asymptotic...
In swainechen/hfufs: Fu's Fs and Strobeck's S Calculators for Arbitrary Parameters
Description
Usage
Arguments
Details
Value
References
Examples
Description
Returns Fu's Fs statistic.
Usage
1
afufs(n, k, theta)
Arguments
n
The number of total sequences/individuals
k
The number of unique alleles
theta
The average pairwise nucleotide divergence
Details
Fu's Fs is a population genetics statistic that is useful for detecting
loci that are responsible for population expansion, for example. Fu's Fs
can be formulated as a calculation that involves Stirling numbers of the
first kind. These can get large very quickly and exceed the floating point
range for modern genomic data sets.
‘afufs' calculates Fu’s Fs using a single term asymptotic approximation
This contrasts with 'hfufs' which uses a Stirling number approximator for
each term. 'afufs' is therefore simultaneously more accurate and faster.
Value
Fu's Fs
References
Chen, S.L. and Temme, N. (2020) Computing sums of Stirling numbers of the
first kind: Application to population genetics statistics. In preparation.
Examples
1
2
3
4
5
n <- 100
k <- 30
theta <- 12.345
afufs(n, k, theta)
# -0.7368616
swainechen/hfufs documentation built on June 22, 2020, 7:02 a.m.
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Description Usage Arguments Details Value References Examples
Description
Returns Fu's Fs statistic.
Usage
1 | afufs(n, k, theta)
|
Arguments
n |
The number of total sequences/individuals |
k |
The number of unique alleles |
theta |
The average pairwise nucleotide divergence |
Details
Fu's Fs is a population genetics statistic that is useful for detecting loci that are responsible for population expansion, for example. Fu's Fs can be formulated as a calculation that involves Stirling numbers of the first kind. These can get large very quickly and exceed the floating point range for modern genomic data sets.
‘afufs' calculates Fu’s Fs using a single term asymptotic approximation This contrasts with 'hfufs' which uses a Stirling number approximator for each term. 'afufs' is therefore simultaneously more accurate and faster.
Value
Fu's Fs
References
Chen, S.L. and Temme, N. (2020) Computing sums of Stirling numbers of the first kind: Application to population genetics statistics. In preparation.
Examples
1 2 3 4 5 | n <- 100
k <- 30
theta <- 12.345
afufs(n, k, theta)
# -0.7368616
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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