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

View source: R/findCopyNumber.R

Given enrichment scores between two groups of samples and the chromosomical positions of those enrichment scores this function finds areas where the enrichemnt is bigger/lower than expected if the positions where assigned at random. Plots of the regions and positions of the enriched regions are provided.

1 2 3 4 | ```
findCopyNumber(x, minGenes = 15, B = 100, p.adjust.method = "BH",
pvalcutoff = 0.05, exprScorecutoff = NA, mc.cores = 1, useAllPerm = F,
genome = "hg19", chrLengths, sampleGenome = TRUE, useOneChr = FALSE,
useIntegrate = TRUE,plot=TRUE,minGenesPerChr=100)
``` |

`x` |
An object of class |

`minGenes` |
Minimum number of genes in a row that have to be enriched to mark the region as enriched. Has to be bigger than 2. |

`B` |
Number of permuations that will be computed to calculate pvalues.
If |

`p.adjust.method` |
P value adjustment method to be used. p.adjust.methods provides a list of available methods. |

`pvalcutoff` |
All genes with an adjusted p value lower than this parameter will be considered enriched. |

`exprScorecutoff` |
Genes with a smoothed score that is not bigger (lower if the given number is negative) than the specified value will not be considered significant. |

`mc.cores` |
Number of cores to be used in the computation. If |

`useAllPerm` |
If FALSE for each gene only permutations of genes that are in an area with similar density (similar number of genes close to them) are used to compute pvalues. If TRUE all permutations are used for each gene. We recommend to use the option FALSE after having observed that the enrichment can depend on the number of genes that are in the area. We recommend to use the option TRUE if the positions of the enrichment
score are equidistant. Take into account that this option is much slower
and needs less permutations, therefore a smaller See details for more info. |

`genome` |
Genome that will be used to draw cytobands. |

`chrLengths` |
An object of class |

`sampleGenome` |
If positions are sampled over the hole genome (across chromosomes) or within each chromosome. This is TRUE by default. |

`useOneChr` |
Use only one chromosome to build the distribution under the null hypothesis that genes/probes are not enriched. By default this is FALSE. The chromosome that is used is chosen as follows: after removing small chromosomes we select the one closest to the median quadratic distance to 0. Setting this parameter to TRUE decreases processing time. |

`useIntegrate` |
If we want to use |

`plot` |
If FALSE the function will make no plots. |

`minGenesPerChr` |
Chromosomes with less than |

Enrichemnt scores can be either log fold changes, log hazard ratios, log variabiliy ratios or any other score.

Within each chromosome a smoothed score for each gene is obtained via generalized additive models, the smoothing parameter for each chromosome being chosen via cross-validation. The obtained smoothing parameter of each chromosome will be used in permutations.

We assessed statistical significance by permuting the positions thrue
the hole genome.
If `useAllPerm`

is FALSE for each gene the permutations of genes
that are in an area with similar density (distance to tenth gene) are
used to compute pvalues. We observed that genes with similar densities
tend to have similar smoothed scores.
If we set 1000 permutations (`B`

=1000) scores are permuted thrue
the hole genome 10 times (1000/100). For each smoothed scored the
permutations of the 100 smoothed scores with most similar density
(distance to tenth gene) are used. Therefore each smoothed score will be
compared to 1000 smoothed scores obtained from permutations.

If scores are at the same distance in the genome from each other (for
instance when we have a score every fixed certain bases) the option
`useAllPerm`

=TRUE is recommended. In this case every smoothed score
is compared to all smoothed scores obtained via permutations.
In this case having 20,000 genes and setting the paramter `B=10`

would mean that the scores are permuted 10 times times thrue the hole
genome, obtaining 200,000 permuted smoothed scores. Each observed smoothed
score will be tested against the distribution of the 200,000 permuted
smoothed scores.

Only regions with as many genes as told in `minGenes`

being
statistically significant (pvalue lower than parameter
`pvalcutoff`

) after adjusting pvalues with the method specified in
`p.adjust.method`

will be selected as enriched.
If `exprScorecutoff`

is different form NA, a gene to be
statistically significant will need (aditionally to the pvalue cutoff)
to have a smoothed score bigger (lower if `exprScorecutoff`

is
negative) than the specified value.

Plots all chromomes and marks the enriched regions.
Also returns a `data.frame`

containing the positions of the
enriched regions. This output can be passed by to the `genesInArea`

function to obtain the names of the genes that are in each region.

Evarist Planet

getEsPositions, genesInArea

1 2 3 4 5 6 7 8 9 | ```
data(epheno)
phenoNames(epheno)
mypos <- getEsPositions(epheno,'Relapse')
mypos$chr <- '1' #we set all probes to chr one for illustration purposes
#(we want a minimum number of probes per chromosome)
head(mypos)
set.seed(1)
regions <- findCopyNumber(mypos,B=10,plot=FALSE)
head(regions)
``` |

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