Runs the default filtering, normalization, and computational steps on a
HiCDOCDataSet
. To learn more about HiCDOC, browse the vignette:
browseVignettes(package = "HiCDOC")
.
HiCDOC(object, parallel = TRUE)
object | A |
---|---|
parallel | Whether or not to parallelize each step. Defaults to TRUE. |
A HiCDOCDataSet with all slots filled.
HiCDOC
pipelineThe HiCDOC pipeline has seven steps:
filterSmallChromosomes
to filter out small chromosomes
filterWeakPositions
to filter out weak positions with very few interactions
filterSparseReplicates
to filter out sparse replicates with many null
interactions
normalizeTechnicalBiases
to normalize technical biases in each replicates
normalizeBiologicalBiases
to normalize biological biases in each replicate
normalizeDistanceEffect
to normalize the distance effect in each chromosome
detectCompartments
to detect compartments in each condition and find
significant changes between conditions.
The parallel version of HiCDOC uses the
BiocParallel
package. Before to call the
function in parallel you should specify the parallel parameters such as:
On Linux: multiParam <- BiocParallel::MulticoreParam(workers = 10)
On Windows: multiParam <- BiocParallel::SnowParam(workers = 10)
And then you can register the parameters to be used by BiocParallel:
BiocParallel::register(multiParam, default = TRUE)
You should be aware that using MulticoreParam, reproducibility of the detectCompartments function using a RNGseed may not work. See this issue for more details.
HiCDOCDataSet
, filterSmallChromosomes
,
filterWeakPositions
, filterSparseReplicates
,
normalizeTechnicalBiases
,
normalizeBiologicalBiases
,
normalizeDistanceEffect
,
detectCompartments
#>#>#>#>#>#>#>#> #> #> #>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#># Equivalent to if(FALSE){ object <- filterSmallChromosomes(exampleHiCDOCDataSet) object <- filterSparseReplicates(object) object <- filterWeakPositions(object) object <- normalizeTechnicalBiases(object) object <- normalizeBiologicalBiases(object) object <- normalizeDistanceEffect(object) object <- detectCompartments(object) }