Description Usage Arguments Details Value References Examples

View source: R/reduce_markers.R

Find the largest subset of markers such that no two adjacent markers are separated by less than some distance.

1 2 3 4 5 6 7 8 | ```
reduce_markers(
map,
min_distance = 1,
weights = NULL,
max_batch = 10000,
batch_distance_mult = 1,
cores = 1
)
``` |

`map` |
A list with each component being a vector with the marker positions for a chromosome. |

`min_distance` |
Minimum distance between markers. |

`weights` |
A (optional) list of weights on the markers; same
size as |

`max_batch` |
Maximum number of markers to consider in a batch |

`batch_distance_mult` |
If working with batches of markers,
reduce |

`cores` |
Number of CPU cores to use, for parallel calculations.
(If |

Uses a dynamic programming algorithm to find, for each
chromosome, the subset of markers for with max(`weights`

) is
maximal, subject to the constraint that no two adjacent markers may
be separated by more than `min_distance`

.

The computation time for the algorithm grows with like the square
of the number of markers, like 1 sec for 10k markers
but 30 sec for 50k markers. If the number of markers on a chromosome
is greater than `max_batch`

, the markers are split into batches and
the algorithm applied to each batch with min_distance smaller by a
factor `min_distance_mult`

, and then merged together for one last pass.

A list like the input `map`

, but with the selected
subset of markers.

Broman KW, Weber JL (1999) Method for constructing confidently ordered linkage maps. Genet Epidemiol 16:337–343

1 2 3 4 5 6 7 8 9 10 11 12 | ```
# read data
grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2"))
# grab genetic map
gmap <- grav2$gmap
# subset to markers that are >= 1 cM apart
gmap_sub <- reduce_markers(gmap, 1)
# drop all of the other markers from the cross
markers2keep <- unlist(lapply(gmap_sub, names))
grav2_sub <- pull_markers(grav2, markers2keep)
``` |

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