pairscan {cape} | R Documentation |

This function performs the pairwise regression on all selected marker pairs. The phenotypes used can be either eigentraits or raw phenotypes. Permutation testing is also performed.

pairscan( data_obj, geno_obj = NULL, scan_what = c("eigentraits", "raw_traits"), pairscan_null_size = NULL, max_pair_cor = NULL, min_per_genotype = NULL, kin_obj = NULL, num_pairs_limit = 1e+06, num_perm_limit = 1e+07, overwrite_alert = TRUE, run_parallel = FALSE, n_cores = 4, verbose = FALSE )

`data_obj` |
a |

`geno_obj` |
a genotype object |

`scan_what` |
A character string uniquely identifying whether eigentraits or raw traits should be scanned. Options are "eigentraits", "raw_traits" |

`pairscan_null_size` |
The total size of the null distribution. This is DIFFERENT than the number of permutations to run. Each permutation generates n choose 2 elements for the pairscan. So for example, a permutation that tests 100 pairs of markers will generate a null distribution of size 4950. This process is repeated until the total null size is reached. If the null size is set to 5000, two permutations of 100 markers would be done to get to a null distribution size of 5000. |

`max_pair_cor` |
A numeric value between 0 and 1 indicating the maximum Pearson correlation that two markers are allowed. If the correlation between a pair of markers exceeds this threshold, the pair is not tested. If this value is set to NULL, min_per_genotype must have a numeric value. |

`min_per_genotype` |
The minimum number of individuals allowable per genotype combination. If for a given marker pair, one of the genotype combinations is underrepresented, the marker pair is not tested. If this value is NULL, max_pair_cor must have a numeric value. |

`kin_obj` |
a kinship object calculated by |

`num_pairs_limit` |
A number indicating the maximum number of pairs to scan. If the number of pairs exceeds this threshold, the function asks for confirmation before proceeding with the pairwise scan. |

`num_perm_limit` |
A number indicating the maximum number of total permutations that will be performed. If the number of total permutations exceeds this threshold, the function asks for confirmation before proceeding with the pairwise scan. |

`overwrite_alert` |
If TRUE raises a warning to users not to overwrite their data object with a singlescan object. A warning necessary after a new version of cape began separating results from different functions into different results objects |

`run_parallel` |
Whether to run the analysis on parallel CPUs |

`n_cores` |
The number of CPUs to use if run_parallel is TRUE |

`verbose` |
Whether to write progress to the screen |

Not all marker pairs are necessarily tested. Before markers are tested for interaction, they are checked for several conditions. Pairs are discarded if (1) at least one of the markers is on the X chromosome, or (2) there are fewer than min_per_genotype individuals in any of the genotype combinations.

This function returns an object assigned to pairscan_obj in
`run_cape`

.

The results object is a list of five elements: ref_allele: The allele used as the reference for the tests. max_pair_cor: The maximum pairwise correlation between marker pairs pairscan_results: A list with one element per trait. The element for each trait is a list of the following three elements: pairscan_effects: the effect sizes from the linear models pairscan_se: the standard errors from the linear models model_covariance: the model covariance from the linear models. pairscan_perm: The same structure as pairscan_results, but for the permuted data. pairs_tested_perm: A matrix of the marker pairs used in the permutation tests.

`select_markers_for_pairscan`

, `plot_pairscan`

## Not run: pairscan_obj <- pairscan(data_obj, geno_obj, pairscan_null_size = 10000) ## End(Not run)

[Package *cape* version 3.1.0 Index]