Advanced

Continuous-index hidden Markov modelling of array CGH copy number data.

Stjernqvist, Susann LU ; Rydén, Tobias LU ; Sköld, Martin LU and Staaf, Johan LU (2007) In Bioinformatics 23. p.1006-1014
Abstract
Motivation: In recent years, a range of techniques for analysis and segmentation of array comparative genomic hybridization (aCGH) data have been proposed. For array designs in which clones are of unequal lengths, are unevenly spaced or overlap, the discrete-index view typically adopted by such methods may be questionable or improved. Results: We describe a continuous-index hidden Markov model for aCGH data as well as a Monte Carlo EM algorithm to estimate its parameters. It is shown that for a dataset from the BT-474 cell line analysed on 32K BAC tiling microarrays, this model yields considerably better model fit in terms of lag-1 residual autocorrelations compared to a discrete-index HMM, and it is also shown how to use the model for... (More)
Motivation: In recent years, a range of techniques for analysis and segmentation of array comparative genomic hybridization (aCGH) data have been proposed. For array designs in which clones are of unequal lengths, are unevenly spaced or overlap, the discrete-index view typically adopted by such methods may be questionable or improved. Results: We describe a continuous-index hidden Markov model for aCGH data as well as a Monte Carlo EM algorithm to estimate its parameters. It is shown that for a dataset from the BT-474 cell line analysed on 32K BAC tiling microarrays, this model yields considerably better model fit in terms of lag-1 residual autocorrelations compared to a discrete-index HMM, and it is also shown how to use the model for e.g. estimation of change points on the base-pair scale and for estimation of conditional state probabilities across the genome. In addition, the model is applied to the Glioblastoma Multiforme data used in the comparative study by Lai et al. (Lai,W.R. et al. (2005) Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data. Bioinformatics, 21, 3763-3370.) giving result similar to theirs but with certain features highlighted in the continuous-index setting. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Bioinformatics
volume
23
pages
1006 - 1014
publisher
Oxford University Press
external identifiers
  • wos:000246293000012
  • scopus:34249681894
ISSN
1367-4803
DOI
10.1093/bioinformatics/btm059
language
English
LU publication?
yes
id
598645fb-cb64-41c7-af48-66e123fda189 (old id 165569)
date added to LUP
2007-07-24 10:40:50
date last changed
2017-01-15 03:39:15
@article{598645fb-cb64-41c7-af48-66e123fda189,
  abstract     = {Motivation: In recent years, a range of techniques for analysis and segmentation of array comparative genomic hybridization (aCGH) data have been proposed. For array designs in which clones are of unequal lengths, are unevenly spaced or overlap, the discrete-index view typically adopted by such methods may be questionable or improved. Results: We describe a continuous-index hidden Markov model for aCGH data as well as a Monte Carlo EM algorithm to estimate its parameters. It is shown that for a dataset from the BT-474 cell line analysed on 32K BAC tiling microarrays, this model yields considerably better model fit in terms of lag-1 residual autocorrelations compared to a discrete-index HMM, and it is also shown how to use the model for e.g. estimation of change points on the base-pair scale and for estimation of conditional state probabilities across the genome. In addition, the model is applied to the Glioblastoma Multiforme data used in the comparative study by Lai et al. (Lai,W.R. et al. (2005) Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data. Bioinformatics, 21, 3763-3370.) giving result similar to theirs but with certain features highlighted in the continuous-index setting.},
  author       = {Stjernqvist, Susann and Rydén, Tobias and Sköld, Martin and Staaf, Johan},
  issn         = {1367-4803},
  language     = {eng},
  pages        = {1006--1014},
  publisher    = {Oxford University Press},
  series       = {Bioinformatics},
  title        = {Continuous-index hidden Markov modelling of array CGH copy number data.},
  url          = {http://dx.doi.org/10.1093/bioinformatics/btm059},
  volume       = {23},
  year         = {2007},
}