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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