Description Usage Arguments Details Value Note Author(s) See Also Examples

View source: R/plot.minPtest.R

plot method for an object of class 'minPtest'. Plots allowing to get an impression of important genes or/and SNPs.

1 2 3 4 5 |

`x` |
an object of class |

`type` |
by default, permutation-based p-values for each gene are plotted ( |

`level` |
a numeric threshold that specifies which genes or/and SNPs are highlighted in the plot. I.e. not depending on the used |

`lambda` |
only useful for |

`gene.name` |
only useful for |

`sigPch` |
Type of plotting for significant permutation-based p-values ( |

`nonsigPch` |
Type of plotting for non significant permutation-based p-values ( |

`pch` |
Set type of plotting for both |

`sigLty` |
only used for |

`nonsigLty` |
only used for |

`lty` |
only used for |

`sigCol` |
Color for significant genes or/and significant SNPs (if neither |

`nonsigCol` |
Color for non significant genes or/and non significant SNPs (if neither |

`col` |
Set color for both |

`xlab` |
xlab (Default: Gene if |

`...` |
Further arguments for the plot function. |

The function plots either `(-log_{10})`

transformed permutation-based p-values for each gene or `(-log_{10})`

transformed marginal p-values for each SNP in a basic scatterplot. The y-axis is `(-log_{10})`

transformed to obtain a disposition as a Manhattan plot for the points of the marginal p-values of the SNPs. Furthermore, an alternative given by the function is to display the marginal p-values for each SNP and the transformed permutation-based p-values for each gene in a combined plot. The `(-log_{10})`

transformed marginal p-values for each SNP are plotted as points. In addition, horizontal lines of `(-lambda*log_{10})`

transformed permutation-based p-values of each gene, covering all SNPs located on that gene, are plotted. The composed plot is indicated by two separated y-axes (`(-log_{10}(psnp))`

at left hand side and `(-lambda*log_{10}(minp))`

at the right hand side). After correction for multiple hypothesis testing depending on the `level`

and the argument `adj.method`

in the `minPtest`

function, but not depending on the used type of plot, significant genes and SNPs are by default highlighted in red, i.e. each permutation-based p-value or/and marginal p-value smaller than or equal to the `level`

, respectively, is highlighted in red.

No value returned

The default for `gene.name=FALSE`

, used for `type="SNP"`

and `type="both"`

, should kept for performance reasons, if a large number of genes are included in the fit. For `type="both"`

no `ylim`

should be specified as the plot is indicated by two separate y-axes.

Stefanie Hieke hieke@imbi.uni-freiburg.de

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | ```
## Continuing the example from minPtest and generateSNPs:
# generate a data set consisting of 100 subjects and 200 SNPs on 5 genes.
SNP <- c(6,26,54,135,156,186)
BETA <- c(0.9,0.7,1.5,0.5,0.6,0.8)
SNPtoBETA <- matrix(c(SNP,BETA),ncol=2,nrow=6)
colnames(SNPtoBETA) <- c("SNP.item","SNP.beta")
set.seed(191)
sim1 <- generateSNPs(n=100,gene.no=5,block.no=4,block.size=10,p.same=0.9,
p.different=0.75,p.minor=c(0.1,0.4,0.1,0.4),
n.sample=80,SNPtoBETA=SNPtoBETA)
# Cochran Armitage Trend Test without covariates and default permutations.
# Example: Run R sequential
### Seed
set.seed(10)
seed1 <- sample(1:1e7,size=1000)
###
minPtest.object <- minPtest(y=sim1$y, x=sim1$x, SNPtoGene=sim1$SNPtoGene,
seed=seed1)
### Combined plot for permutation-based p-values and marginal p-values.
plot(minPtest.object,type="both",lambda=0.5,gene.name=TRUE)
## Combined plot for permutation-based p-values and marginal
## p-values. Plot permutation-based p-values and significant marginal
## p-values as blue dotted lines and blue points
## plot(minPtest.object,type="both",lambda=0.5,
## gene.name=TRUE,sigCol="blue",sigLty=2)
``` |

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