Description Usage Arguments Details Value Examples

This function simply returns the weighted mean inbreeding coefficient *f_j^T*.
If no weights are provided, the regular mean *f_j^T* is returned.
If a kinship matrix *Φ^T* is provided, then *f_j^T* are extracted from its diagonal using `inbr`

(assumes the diagonal of *Φ^T* is *φ_jj^T = (1+f_j^T)/2* as `popkin`

returns, and not *f_j^T* as `inbrDiag`

returns).

1 | ```
fst(x, w)
``` |

`x` |
The vector of inbreeding coefficients |

`w` |
Weights for individuals (optional, defaults to uniform weights) |

The returned weighted mean inbreeding coefficient equals the generalized *FST* if all individuals are "locally outbred" (i.e. if the self relatedness of every individual stems entirely from the population structure rather than due partly to having unusually closely related parents, such as first or second cousins).
Note most individuals in population-scale human data are locally outbred.
If there are locally inbred individuals, the returned value will overestimate *FST*.

*FST*

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
## Get FST from a genotype matrix
## Construct toy data
X <- matrix(c(0,1,2,1,0,1,1,0,2), nrow=3, byrow=TRUE) # genotype matrix
subpops <- c(1,1,2) # subpopulation assignments for individuals
## NOTE: for BED-formatted input, use BEDMatrix!
## "file" is path to BED file (excluding .bed extension)
# library(BEDMatrix)
# X <- BEDMatrix(file) # load genotype matrix object
## estimate the kinship matrix "Phi" from the genotypes "X"!
Phi <- popkin(X, subpops) # calculate kinship from X and optional subpop labels
w <- weightsSubpops(subpops) # can weigh individuals so subpopulations are balanced
Fst <- fst(Phi, w) # use kinship matrix and weights to calculate fst
Fst <- fst(Phi) # no weights implies uniform weights
inbr <- inbr(Phi) # if you extracted inbr for some other analysis...
Fst <- fst(inbr, w) # ...use this inbreeding vector as input too!
``` |

popkin documentation built on Jan. 27, 2018, 1:03 a.m.

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