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:
https://lup.lub.lu.se/record/165569
- author
- Stjernqvist, Susann
LU
; Rydén, Tobias
LU
; Sköld, Martin
LU
and Staaf, Johan
LU
- organization
- publishing date
- 2007
- 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
- pmid:17309894
- 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
- 2016-04-01 12:24:38
- date last changed
- 2022-01-27 03:21:56
@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}},
doi = {{10.1093/bioinformatics/btm059}},
volume = {{23}},
year = {{2007}},
}