ChiapetExperimentData class is a container for storing the set of raw data used by 3CPET to do the prediction.
ChiapetExperimentData(pet='', tfbs='', ppi=NULL, ## loadPETs options IsBed=TRUE, petHasHeader=FALSE, dist=1000, ## loadTFBS options tfbsHasHeader=FALSE, ## loadPPI options ppiType=c("HPRD","Biogid"), filter=FALSE, term="GO:0005634", annot=NULL, RPKM= NULL, threshold=1 )GRanges object. The GRanges object should have a metadata column named TF.igraph object that contains a user defined protein-protein interaction network.
if this parameter is not specified, the ppiType paramter will be used.pet parameter is a file path.
More info about this paramters can be found in the loadPETs help page. logical. Indicates if the ChIA-PET interactions file has a header or not.logical. Indicates if the TFBS file has a header or not.ppi paramter is not specified.
This paramter tell the pakage to load one of the PPI (HPRD or Biogrid) shiped with the package. logical. whether of not to filter the PPI network.
if the RPKM paramter is specified then the RPKM dataset incorporated with the package will be used.
if you want to to your own way of filtering, you ca set filter = FALSE and pass an already processed PPI
to the ppi paramterer.filter parameter.
in the filter parameter the PPI nodes are filtered by their gene expression, while in the term parameter
they are filtered by their genomic location. by default "GO:0005634" is used for filtering.geneLocations is used.
The user can pass a custom data.frame. For more details check the loadPPI help page.ChiapetExperimentData object with the specified fields populated.
GRanges that stores the genomic coordinated of the interactions.
it can be populated using the method loadPETsGRanges that stores the TF binding site.
it can be populated using the method loadTFBS.
NOTE: the TFBS locations can be obtained from a ChIP-Seq experiment or a motif finding software.
for more information on the format of the provided data check loadTFBS"igraph" used as the background PPI for further analysis.
it can be populated using the method loadPPI "list" contains a collection of data.table
serving as indexes used internally by the package (not expected to be manipulated by the user).
it can be populated using the method createIndexes ChiapetExperimentData object x :
pet(x), pet(x) <- value:
Get ChIA-PET interactions encoded as a GRanges object in x. The returned GRanges objects
contains an attribute PET_ID in which the left side have an id of the form PET#\d+\.1
and the right side interaction have an id of the form PET#\d+\.2. for more information check loadPETs
seqnames ranges strand | PET_ID
|
[1] chr1 [1240734, 1242734] * | PET#1.1
[2] chr1 [1242224, 1244224] * | PET#1.2
[3] chr1 [1282208, 1284208] * | PET#2.1
[4] chr1 [1283334, 1285334] * | PET#2.2
[5] chr1 [1370371, 1372371] * | PET#3.1
[6] chr1 [1371822, 1373822] * | PET#3.2
tfbs(x), tfbs(x) <- value:
Get the GRanges storing the transcription factor binding sites.
ppi(x), ppi(x) <- value:
Returns an igraph object used as a background PPI. check the loadPPI for more information.
ChiapetExperimentData class stores the genomic coordinates of the
ChIA-PET interactions, the binding sites of the different transcription factor (TFBS)
and the background protein-protein interaction (PPI) network used to infer the final
chromatin maintainer networks.
Mohamed Nadhir D, Yang C et al 3CPET: Finding Co-factor Complexes in Chia-PET experiment using a Hierarchical Dirichlet Process, ....
loadPETs, loadTFBS , loadPPI
## for example Reading ChIA-PET interaction results generated from ChIA-PET tool
## it should be formatted as follow:
## -------------------------------------------------------------------------------------------
## chromleft startleft endleft chromright startright endright counts pvalue qvalue
## chr1 872113 879175 chr1 933836 938416 12 1.84529e-30 6.90983e-28
## chr1 874165 879175 chr1 933340 938306 10 1.23139e-25 3.58932e-23
## chr1 889676 896594 chr1 933897 938982 13 4.91311e-36 2.33753e-33
## chr1 898753 907581 chr1 931133 939571 19 0.00000e+00 0.00000e+00
## chr1 910103 918775 chr1 930834 938627 15 2.20004e-43 1.32812e-40
## chr1 919314 922154 chr1 934212 937864 6 3.70292e-21 7.88551e-19
##---------------------------------------------------------------------------------------------
## The counts, pvalue and qvalue fields are not considered in our case
## it is up to the user to filter the interactions.
## The TFBS should be a BED file that contain the chromosome, start, end and the TF name
## Not run:
#
# ## load the different datasets
# petFile <- file.path(system.file("example",package="R3CPET"),"HepG2_interactions.txt")
# tfbsFile <- file.path(system.file("example",package="R3CPET"),"HepG2_TF.txt.gz")
#
# x <- ChiapetExperimentData(pet = petFile, tfbs= tfbsFile, IsBed = FALSE, ppiType="HPRD", filter= TRUE)
# ## build the diffrent indexes
# x <- createIndexes(x)
# x
#
# ## Pass objects instead of files.
# pet <- sample(pet(x),size = 20,replace = TRUE )
# tfbs <- sample(tfbs(x), size=300, replace=TRUE)
# ppi <- ppi(x)
# tst <- ChiapetExperimentData(pet = pet, tfbs= tfbs, ppi=ppi)
# tst <- createIndexes(tst)
# tst
# ## End(Not run)
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