seqhap | R Documentation |

Seqhap implements sequential haplotype scan methods to perform association analyses for case-control data. When evaluating each locus, loci that contribute additional information to haplotype associations with disease status will be added sequentially. This conditional evaluation is based on the Mantel-Haenszel (MH) test. Two sequential methods are provided, a sequential haplotype method and a sequential summary method, as well as results based on the traditional single-locus method. Currently, seqhap only works with bialleleic loci (single nucleotide polymorphisms, or SNPs) and binary traits.

seqhap(y, geno, pos, locus.label=NA, weight=NULL, mh.threshold=3.84, r2.threshold=0.95, haplo.freq.min=0.005, miss.val=c(0, NA), sim.control=score.sim.control(), control=haplo.em.control()) ## S3 method for class 'seqhap' print(x, digits=max(options()$digits-2, 5), ...)

`y` |
vector of binary response (1=case, 0=control). The length is equal to the number of rows in geno. |

`geno` |
matrix of alleles, such that each locus has a pair of adjacent columns of alleles, and the order of columns corresponds to the order of loci on a chromosome. If there are K loci, then ncol(geno)=2*K. Rows represent the alleles for each subject. Currently, only bi-allelic loci (SNPs) are allowed. |

`pos` |
vector of physical positions (or relative physical positions) for loci. If there are K loci, length(pos)=K. The scale (in kb, bp, or etc.) doesn't affect the results. |

`locus.label ` |
vector of labels for the set of loci |

`weight` |
weights for observations (rows of geno matrix). |

`mh.threshold ` |
threshold for the Mantel-Haenszel statistic that evaluates whether a locus contributes additional information of haplotype association to disease, conditional on current haplotypes. The default is 3.84, which is the 95th percentile of the chi-square distribution with 1 degree of freedom. |

`r2.threshold ` |
threshold for a locus to be skipped. When scanning locus k, loci with correlations r-squared (the square of the Pearson's correlation) greater than r2.threshold with locus k will be ignored, so that the haplotype growing process continues for markers that are further away from locus k. |

`haplo.freq.min ` |
the minimum haplotype frequency for a haplotype to be included in the association tests. The haplotype frequency is based on the EM algorithm that estimates haplotype frequencies independent of trait. |

`miss.val ` |
vector of values that represent missing alleles. |

`sim.control` |
A list of control parameters to determine how simulations are performed for permutation p-values, similar to the strategy in haplo.score. The list is created by the function score.sim.control and the default values of this function can be changed as desired. Permutations are performed until a p.threshold accuracy rate is met for the three region-based p-values calculated in seqhap. See score.sim.control for details. |

`control` |
A list of parameters that control the EM algorithm for estimating haplotype frequencies when phase is unknown. The list is created by the function haplo.em.control - see this function for more details. |

`x` |
a seqhap object to print |

`digits` |
Number of significant digits to print for numeric values |

`... ` |
Additional parameters for the print method |

No further details

list with components:

`converge` |
indicator of convergence of the EM algorithm (see haplo.em); 1 = converge, 0=failed |

`locus.label` |
vector of labels for loci |

`pos` |
chromosome positions for loci, same as input. |

`n.sim` |
number of permutations performed for emperical p-values |

`inlist` |
matrix that shows which loci are combined for association analysis in the sequential scan. The non-zero values of the kth row of inlist are the indices of the loci combined when scanning locus k. |

`chi.stat` |
chi-square statistics of single-locus analysis. |

`chi.p.point` |
permuted pointwise p-values of single-locus analysis. |

`chi.p.region` |
permuted regional p-value of single-locus analysis. |

`hap.stat` |
chi-square statistics of sequential haplotype analysis. |

`hap.df` |
degrees of freedom of sequential haplotype analysis. |

`hap.p.point` |
permuted pointwise p-values of sequential haplotype analysis. |

`hap.p.region` |
permuted region p-value of sequential haplotype analysis. |

`sum.stat` |
chi-square statistics of sequential summary analysis. |

`sum.df` |
degrees of freedom of sequential summary analysis. |

`sum.p.point` |
permuted pointwise p-values of sequential summary analysis. |

`sum.p.region` |
permuted regional p-value of sequential summary analysis. |

Yu Z, Schaid DJ. (2007) Sequential haplotype scan methods for association analysis. Genet Epidemiol, in print.

`haplo.em`

,
`print.seqhap`

,
`plot.seqhap`

,
`score.sim.control`

# load example data with response and genotypes. data(seqhap.dat) mydata.y <- seqhap.dat[,1] mydata.x <- seqhap.dat[,-1] # load positions data(seqhap.pos) pos <- seqhap.pos$pos # run seqhap with default settings ## Not run: # this example takes 5-10 seconds to run myobj <- seqhap(y=mydata.y, geno=mydata.x, pos=pos) print.seqhap(myobj) ## End(Not run)

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