Description Usage Arguments Value Author(s) References See Also Examples
View source: R/GenometriCorrelation.R
The GenometriCorrelation function compares two interval annotations on a chromosome, set of chromosomes or on an entire genome, and performs various statistical tests to determine whether the two interval sets are independent or are positioned nonrandomly with respect to each other. For a complete description of the tests, refer to the the package vignette.
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  GenometriCorrelation(
query,
reference,
chromosomes.to.proceed = c(),
chromosomes.to.include.in.awhole = c(),
chromosomes.to.exclude.from.awhole = c(),
add.chr.as.prefix = FALSE,
awhole.only = FALSE,
map.to.half = TRUE,
showProgressBar = TRUE,
showTkProgressBar = FALSE,
chromosomes.length = c(),
suppress.evaluated.length.warning = FALSE,
permut.number = 100,
ecdf.area.permut.number = permut.number,
mean.distance.permut.number = permut.number,
jaccard.measure.permut.number = permut.number,
jaccard.permut.is.rearrangement = FALSE,
alternative = "two.sided",
awhole.space.name = "awhole",
keep.distributions = FALSE,
representing.point.function = mitl,
query.representing.point.function = representing.point.function,
reference.representing.point.function = representing.point.function,
supress.evaluated.length.warning
)

query 
GRanges object that contains the query interval set coordinates and spaces (generally, chromosomes). The 
reference 
The 
chromosomes.to.proceed 
This vector of strings contains the names of spaces (chromosomes) to analyze. If both 
chromosomes.to.include.in.awhole 
ia a vector of strings contains the names of spaces to be included in the overall (awhole) statistics. Its default is c(), meaning that all the analysed genes are included. 
chromosomes.to.exclude.from.awhole 
is a list of chromosomes (spaces) to be excluded from the overall statistics. 
add.chr.as.prefix 
deals with the chr chromosome name prefix. The correlation is only performed on chromosomes that have exactly the same name, so by default, a chromosome named chr1 will not be considered the same chromosome as one simply labeled 1. This argument is provided so that if the chromosome names in the 
awhole.only 
If 
map.to.half 
Some of the tests we use are besed on distances between a query point and the closest reference point. If map.to.half is TRUE (default) we look for the closest reference point upstream or downstream, if it is 
showProgressBar 
Toggle the text progress bar. Default is 
showTkProgressBar 
Toggle the Tk progress bar. If it is 
chromosomes.length 
A vector of lengths of the chromosomes to be tested; each chromosome is given a name and a numerical length. The order of the chromosomes does not matter. 
suppress.evaluated.length.warning 
If there is a chromosome that is included in the evaluation but its length is not given in 
permut.number 
is the common default for 
ecdf.area.permut.number 
The number of permutations performed to get the pvalue for the area between the ecdf for relative distance distribution and the straight line representing the uniform relative area for the random case. 
mean.distance.permut.number 
The number of permutations to ascribe pvalue to minimal queryreference distance averaged over all query points. 
jaccard.measure.permut.number 
The number of permutations for Jaccard measure pvalue estimation. 
jaccard.permut.is.rearrangement 
If 
alternative 
a character string specifying the alternative hypothesis, must be one of 
awhole.space.name 
The name of the pseudospace that describes the overall genome statistics. Default is 'awhole'. 
keep.distributions 
It this is true, the procedure returns all points in th distributions calculated for comparison. This is useful for making figures. Default is 
representing.point.function 
By default, the midpoint of each interval is used as the surrogate for the position of the interval. To force the program to use something other than the midpoint, define the function to use to return comparison points. The function must take the same parameters as the default 
query.representing.point.function 
The same thing as the 
reference.representing.point.function 
The same thing as the 
supress.evaluated.length.warning 
It was a typo for 
The result is an instance of the GenometriCorrResultclass
that describes the run parameters in its GenometriCorrResultclass
@config
slot and that extends a namedList
list (created originally with a list()
call with the results of the run. Each element of the list is also a list that describes results for a space (chromosome); one of them is 'awhole' (or other awhole.space.name
if given) that describes the genome awhole, all others are named the same as the chromosomes and describe the chromosomewise statistics. The elements of the 'awhole' and chromosomewise lists are statistical measures and some datasets. The statistical measures are described in the GenometriCorr
package help. For further explanation, see the the package vignette.
Below is the description of the values of the list returned for each chromosome.
query.population 
Query points used in the comparisons. 
reference.population 
Reference points used in the comparisons. 
alternative 
Shows the value of the 
relative.distances.ks.p.value 
pvalue for local independence obtained by the KolmogorovSmirnov test for relative distances. 
relative.distances.ecdf.deviation.area.p.value 
pvalue for local independence obtained by the permutation test for relative distances. 
relative.distances.ecdf.deviation.area.test.direction 
"attraction" or "repulsion". If the 
relative.distances.ecdf.area.correlation 
Has the same sign with the relative distancebased local correlation. 
projection.test.p.value 
pvalue for chromosomescale independence obtained by the projection test. 
projection.test.direction 
"attraction" or "repulsion". If the 
projection.test.obs.to.exp 
To measure the effect size, the observed to expected ratio for the projection test statistics that is the number of query characteristic points (by default, midpoints) that fell into a reference features. 
scaled.absolute.min.distance.sum.p.value 
pvalue for chromosomescale null hypothesis as obtained by the permutations of the query points and the mean of the distances to the two closest reference points. 
scaled.absolute.min.distance.sum.test.direction 
"attraction" or "repulsion". If the 
query.reference.intersection 
Intersection of reference and query, in bases. 
query.reference.union 
Union of reference and query, in bases. 
jaccard.measure 
Jaccard measure of query and reference overlap. 
jaccard.measure.p.value 
The permutationbased evaluation of the pvalue for the obtained Jaccard measure, given the null hypothesis of independence. 
jaccard.measure.test.direction 
"attraction" or "repulsion". If the 
The additional values that are returned if keep.distributions=TRUE
relative.distances.data 
The original relative distances 
relative.distances.ecdf.deviation.area 
The real value of the ECDF deviation area to be compared with the permutation to obtain the pvalue 
relative.distances.ecdf.deviation.area.null.list 
The null distribution 
projection.test 
List of three values: 
absolute.min.distance.data 
The distribution of queryreference distances 
absolute.inter.reference.distance.data 
The distribution of referencereference distances 
scaled.absolute.min.distance.sum 
The value of the sum (i.e. mean) of scaled absolute distances 
scaled.absolute.min.distance.sum.null.list 
The null distribution for the scaled absolute distances 
jaccard.measure.null.list 
The null distribution of Jaccard measures in permutations 
Alexander Favorov favorov@sensi.org, Loris Mularoni, Yulia Medvedeva, Harris A. Jaffee, Ekaterina V. Zhuravleva, Veronica Busa, Leslie M. Cope, Andrey A. Mironov, Vsevolod J. Makeev, Sarah J. Wheelan.
The GenometriCorr
documentation and vignette.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15  library('rtracklayer')
library('GenometriCorr')
library('TxDb.Hsapiens.UCSC.hg19.knownGene')
refseq<transcripts(TxDb.Hsapiens.UCSC.hg19.knownGene)
cpgis<import(system.file("extdata", "UCSCcpgis_hg19.bed", package = "GenometriCorr"))
seqinfo(cpgis)<seqinfo(TxDb.Hsapiens.UCSC.hg19.knownGene)[seqnames(seqinfo(cpgis))]
pn.area<10
pn.dist<10
pn.jacc<10
cpgi_to_genes<GenometriCorrelation(cpgis,refseq,chromosomes.to.proceed=c('chr1','chr2','chr3'),ecdf.area.permut.number=pn.area,mean.distance.permut.number=pn.dist,jaccard.measure.permut.number=pn.jacc,keep.distributions=FALSE,showProgressBar=FALSE)
print(cpgi_to_genes)

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