Description Usage Arguments Details Value Author(s) See Also Examples
Fit a deconvolution model.
1 2 3 4 5 6 |
object |
Object of class |
objectMotif |
Object of class |
estDeltaSigma |
Approach to estimate delta and sigma parameters for SET data.
Possible values are either |
init |
Approach to initialize locations of binding events.
Possible values are |
nTop |
Number of candidate regions used to estimate common delta and sigma estimates.
Relevant only when |
lbDelta |
Lower bound for delta parameter. |
lbSigma |
Lower bound for sigma parameter. |
psize |
Approximate size of the binding protein of interest. |
maxComp |
Maximum possible number of binding events in each peak region. |
pConst |
Value to determine the plateau in the BIC curve. Should be a value larger than zero and smaller than one. |
nCore |
Number of CPUs to be used when parallel computing is utilized. |
verbose |
Use verbose mode?
Possible values are either |
iterInit |
Iteration number for initial estimation of binding sites. |
iterMain |
Iteration number for main estimation of binding sites. |
epsilon |
Criterion to stop iteration for binding site estimation. |
... |
Other parameters to be passed through to generic |
Parallel computing can be utilized for faster computation
if parallel package is installed.
Users can change the number of CPUs to be used by changing the argument nCore.
Construct DpeakFit class object.
Dongjun Chung
1 2 | data(exampleData)
exampleFit <- dpeakFit(exampleData, maxComp = 5)
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