Description Usage Arguments Details Value Author(s) See Also
View source: R/callPeaksUnivariate.R
Fit a HMM to a ChIP-seq sample to determine the modification state of genomic regions, e.g. call peaks in the sample.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | callPeaksUnivariateAllChr(
binned.data,
control.data = NULL,
eps = 0.01,
init = "standard",
max.time = NULL,
max.iter = NULL,
num.trials = 1,
eps.try = NULL,
num.threads = 1,
read.cutoff = TRUE,
read.cutoff.quantile = 1,
read.cutoff.absolute = 500,
max.mean = Inf,
post.cutoff = 0.5,
control = FALSE,
keep.posteriors = FALSE,
keep.densities = FALSE,
verbosity = 1
)
|
binned.data |
A |
control.data |
Input control for the experiment. A |
eps |
Convergence threshold for the Baum-Welch algorithm. |
init |
One of the following initialization procedures:
|
max.time |
The maximum running time in seconds for the Baum-Welch algorithm. If this time is reached, the Baum-Welch will terminate after the current iteration finishes. The default |
max.iter |
The maximum number of iterations for the Baum-Welch algorithm. The default |
num.trials |
The number of trials to run the HMM. Each time, the HMM is seeded with different random initial values. The HMM with the best likelihood is given as output. |
eps.try |
If code num.trials is set to greater than 1, |
num.threads |
Number of threads to use. Setting this to >1 may give increased performance. |
read.cutoff |
The default ( |
read.cutoff.quantile |
A quantile between 0 and 1. Should be near 1. Read counts above this quantile will be set to the read count specified by this quantile. Filtering very high read counts increases the performance of the Baum-Welch fitting procedure. However, if your data contains very few peaks they might be filtered out. If option |
read.cutoff.absolute |
Read counts above this value will be set to the read count specified by this value. Filtering very high read counts increases the performance of the Baum-Welch fitting procedure. However, if your data contains very few peaks they might be filtered out. If option |
max.mean |
If |
post.cutoff |
False discovery rate. codeNULL means that the state with maximum posterior probability will be chosen, irrespective of its absolute probability (default=codeNULL). |
control |
If set to |
keep.posteriors |
If set to |
keep.densities |
If set to |
verbosity |
Verbosity level for the fitting procedure. 0 - No output, 1 - Iterations are printed. |
The Hidden Markov Model which is used to classify the bins uses 3 states: state 'zero-inflation' with a delta function as emission densitiy (only zero read counts), 'unmodified' and 'modified' with Negative Binomials as emission densities. A Baum-Welch algorithm is employed to estimate the parameters of the distributions. Please refer to our manuscript at http://dx.doi.org/10.1101/038612 for a detailed description of the method.
A uniHMM
object.
Aaron Taudt, Maria Coome Tatche
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