Description Usage Arguments Details Value Author(s)

View source: R/sqtl.seeker.p.R

`sqtl.seeker.p`

performs the same test as `sqtl.seeker`

between SNPs and
relative transcript expression values, prior permutation of individual labels (see
Details).

1 2 3 4 5 6 7 8 9 10 11 12 | ```
sqtl.seeker.p(
tre.df,
genotype.f,
gene.loc,
covariates = NULL,
genic.window = 5000,
nb.perm.min = 100,
nb.perm.max = 1000,
min.nb.ext.scores = 100,
min.nb.ind.geno = 10,
verbose = FALSE
)
``` |

`tre.df` |
a data.frame with transcript relative expression
produced by |

`genotype.f` |
the name of the genotype file. This file needs to
be ordered by position, compressed and indexed using |

`gene.loc` |
a data.frame with the genes location. Columns 'chr', 'start',
'end' and 'geneId' are required. Same as in |

`covariates` |
a data.frame with covariate information per sample (samples x covariates).
Rownames should be the sample ids. Covariates can be either |

`genic.window` |
the window(bp) around the gene in which the SNPs are tested. Default is 5000 (i.e. 5kb). |

`nb.perm.min` |
the minimum number of permutations. Default is 100. |

`nb.perm.max` |
the maximum number of permutations. Default is 1000. |

`min.nb.ext.scores` |
the minimum number of permuted nominal P-values lower than the lowest observed nominal P-value to allow the computation to stop. Default is 100. |

`min.nb.ind.geno` |
SNPs with less samples than |

`verbose` |
Default is |

`sqtl.seeker.p`

implements an adaptive permutation procedure to control for
multiple testing (i.e. multiple genetic variants are tested per gene, see also
`sqtls.p`

). The outcome of the permutations is then modeled using beta
distributions, as in FastQTL (Ongen et al., 2015), allowing to compute an adjusted
empirical P-value per gene.

A data.frame with columns:

`geneId` |
the gene name. |

`variants.cis` |
the number of variants tested in cis. |

`LD` |
a linkage disequilibrium estimate for the genomic window (median r2). |

`best.snp` |
ID of the SNP with the smallest observed nominal P-value. |

`best.nominal.pv` |
P-value corresponding to the best SNP. |

`shape1` |
Beta distribution parameter shape1. |

`shape2` |
Beta distribution parameter shape2. |

`nb.perms` |
the number of permutations used for the empirical P-value computation. |

`pv.emp` |
empirical P-value based on permutations. |

`pv.emp.beta` |
empirical P-value based on the beta approximation. |

`runtime` |
approximated computation time per gene. |

Diego Garrido-Martín

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