haploNet | R Documentation |

`haploNet`

computes a haplotype network. There is a plot method
and two conversion functions towards other packages.

haploNet(h, d = NULL, getProb = TRUE) ## S3 method for class 'haploNet' print(x, ...) ## S3 method for class 'haploNet' plot(x, size = 1, col, bg, col.link, lwd, lty, shape = "circles", pie = NULL, labels, font, cex, scale.ratio, asp = 1, legend = FALSE, fast = FALSE, show.mutation, threshold = c(1, 2), xy = NULL, ...) ## S3 method for class 'haploNet' as.network(x, directed = FALSE, altlinks = TRUE, ...) ## S3 method for class 'haploNet' as.igraph(x, directed = FALSE, use.labels = TRUE, altlinks = TRUE, ...) ## S3 method for class 'haploNet' as.phylo(x, quiet, ...) ## S3 method for class 'haploNet' as.evonet(x, ...)

`h` |
an object of class |

`d` |
an object giving the distances among haplotypes (see details). |

`getProb` |
a logical specifying whether to calculate Templeton's probabilities (see details). |

`x` |
an object of class |

`size` |
a numeric vector giving the diameter of the circles representing the haplotypes: this is in the same unit than the links and eventually recycled. |

`col` |
a character vector specifying the colours of the circles; eventually recycled. |

`bg` |
a character vector (or a function) specifying either the
colours of the background of the symbols (if |

`col.link` |
a character vector specifying the colours of the links; eventually recycled. |

`lwd` |
a numeric vector giving the width of the links; eventually recycled. |

`lty` |
idem for the line types. |

`shape` |
the symbol shape used for the haplotypes (eventually
recycled): |

`pie` |
a matrix used to draw pie charts for each haplotype; its number of rows must be equal to the number of haplotypes. |

`labels` |
a logical specifying whether to identify the haplotypes with their labels (the default). |

`font` |
the font used for these labels (bold by default); must be an integer between 1 and 4. |

`cex` |
a numerical specifying the character expansion of the labels. |

`scale.ratio` |
the ratio of the scale of the links representing the number of steps on the scale of the circles representing the haplotypes. It may be needed to give a value greater than one to avoid overlapping circles. |

`asp` |
the aspect ratio of the plot. Do not change the default unless you want to distort your network. |

`legend` |
a logical specifying whether to draw the legend, or a
vector of length two giving the coordinates where to draw the
legend; |

`fast` |
a logical specifying whether to optimize the spacing of
the circles; |

`show.mutation` |
an integer value: if 0, nothing is drawn on the links; if 1, the mutations are shown with small segments on the links; if 2, they are shown with small dots; if 3, the number of mutations are printed on the links. |

`threshold` |
a numeric vector with two values (or 0) giving the
lower and upper numbers of mutations for alternative links to be
displayed. If |

`directed` |
a logical specifying whether the network is directed
( |

`use.labels` |
a logical specifying whether to use the original labels in the returned network. |

`altlinks` |
whether to output the alternative links when
converting to another class; |

`quiet` |
whether to give a warning when reticulations are dropped when converting a network into a tree. |

`xy` |
the coordinates of the nodes (see |

`...` |
further arguments passed to |

By default, the haplotype network is built using an infinite site
model (i.e., uncorrected or Hamming distance) of DNA sequences and
pairwise deletion of missing data (see `dist.dna`

).
Users may specify their own distance with the argument `d`

. There
is no check of labels, so the user must make sure that the distances
are ordered in the same way than the haplotypes.

The probabilities calculated with Templeton et al.'s (1992) method may
give non-finite values with very divergent sequences, resulting in an
error from `haploNet`

. If this happens, it may be better to use
`getProb = FALSE`

.

If two haplotypes are very different, `haploNet`

will likely fail
(error during integration due to non-finite values).

`haploNet`

returns an object of class `"haploNet"`

which is
a matrix where each row represents a link in the network, the first
and second columns give the numbers of the linked haplotypes, the
third column, named `"step"`

, gives the number of steps in this
link, and the fourth column, named `"Prob"`

, gives the
probability of a parsimonious link as given by Templeton et
al. (1992). There are three additional attributes: `"freq"`

, the
absolute frequencies of each haplotype, `"labels"`

, their labels,
and `"alter.links"`

, the alternative links of the network.

`as.network`

and `as.igraph`

return objects of the
appropriate class.

Plotting haplotype networks is a difficult task. There is a vignette
in pegas (see `vignette("PlotHaploNet")`

) giving some
information on this isseu. You may also see two posts on r-sig-genetics
(July 2022) that give some tricks in the situation when one haplotype
is abundant and the others are in low frequencies (the symbols are
likely to overlap a lot by default):

https://stat.ethz.ch/pipermail/r-sig-genetics/2022-July/000237.html

https://stat.ethz.ch/pipermail/r-sig-genetics/2022-July/000238.html

The first post explains how to use the package network in combination with pegas, and the second one gives a trick that works with pegas only for a similar result.

Emmanuel Paradis, Klaus Schliep

Templeton, A. R., Crandall, K. A. and Sing, C. F. (1992) A cladistic
analysis of phenotypic association with haplotypes inferred from
restriction endonuclease mapping and DNA sequence data. III. Cladogram
estimation. *Genetics*, **132**, 619–635.

`haplotype`

, `haploFreq`

, `replot`

,
`diffHaplo`

, `mst`

, `mjn`

## generate some artificial data from 'woodmouse': data(woodmouse) x <- woodmouse[sample(15, size = 110, replace = TRUE), ] h <- haplotype(x) (net <- haploNet(h)) plot(net) ## symbol sizes equal to haplotype sizes: plot(net, size = attr(net, "freq"), fast = TRUE) plot(net, size = attr(net, "freq")) plot(net, size = attr(net, "freq"), scale.ratio = 2, cex = 0.8)

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