RIPSeeker (version 1.12.0)

nbh.GRanges: Optimize HMM parameters based on the read counts on a chromosome

Description

Inheritance function from nbh that receives an object of GRanges class with additional column of read counts (for each strand) and call nbh.integer to derive the most probable sequence of hidden states

Usage

## S3 method for class 'GRanges':
nbh(x, K, ...)

Arguments

x

GRanges with 'values' slot used for bin counts in 1D vector of integers.

K

Number of hidden states.

...

Extra arguments passed to nbh.integer for the actual HMM computation.

Value

• binGR
  GRanges of bin counts with metadata slot saved for the optimized HMM parameters including alpha, beta for the K negative binomial mixture components and TRANS (the transition probabilities)

References

Rabiner, L. R. (1989). A tutorial on hidden Markov models and selected applications in speech recognition (Vol. 77, pp. 257-286). Presented at the Proceedings of the IEEE. doi:10.1109/5.18626

Bishop, Christopher. Pattern recognition and machine learning. Number 605-631 in Information Science and Statisitcs. Springer Science, 2006.

Capp'e, O. (2001). H2M : A set of MATLAB/OCTAVE functions for the EM estimation of mixtures and hidden Markov models. (http://perso.telecom-paristech.fr/cappe/h2m/)

See Also

mainSeekSingleChrom, nbh.integer

Examples

if(interactive()) ?nbh # see nbh for example of nbh running on GRanges object