A Modified Bayes Information Criterion with Applications to the Analysis of Comparative Genomic Hybridization Data
Abstract
Summary In the analysis of data generated by change‐point processes, one critical challenge is to determine the number of change‐points. The classic Bayes information criterion (BIC) statistic does not work well here because of irregularities in the likelihood function. By asymptotic approximation of the Bayes factor, we derive a modified BIC for the model of Brownian motion with changing drift. The modified BIC is similar to the classic BIC in the sense that the first term consists of the log likelihood, but it differs in the terms that penalize for model dimension. As an example of application, this new statistic is used to analyze array‐based comparative genomic hybridization (array‐CGH) data. Array‐CGH measures the number of chromosome copies at each genome location of a cell sample, and is useful for finding the regions of genome deletion and amplification in tumor cells. The modified BIC performs well compared to existing methods in accurately choosing the number of regions of changed copy number. Unlike existing methods, it does not rely on tuning parameters or intensive computing. Thus it is impartial and easier to understand and to use.
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Although it has been suggested that second-generation antipsychotics reduce mortality overall, polypharmacy and higher drug dosages may increase it.
“Although it has been suggested that second-generation antipsychotics reduce mortality overall,6 polypharmacy and higher drug dosages may increase it.60”
From Mortality gap for people with bipolar disorder and schizophrenia: UK-based cohort study 2000–2014 (2017) · cites this paper as [6]
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Mortality gap for people with bipolar disorder and schizophrenia: UK-based cohort study 2000–2014
Hayes, J. F., Marston, L., Walters, K., King, M. B., & Osborn, D. P. J. (2017) · British Journal of Psychiatry · doi:10.1192/bjp.bp.117.202606 · Cited by 451 · see citing works
- Authors
- Zhang, N. R., & Siegmund, D. O.
- Affiliations
- Stanford University (US)
- Corresponding author
- Zhang, Nancy R.
- Siegmund, David O.
- Venue
- Biometrics
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-03
- Volume
- 63
- Issue
- 1
- Pages
- 22-32
- ISSN
- 0006-341X (ISSN-L)
- 1541-0420
- OpenAlex
- W2078273711
- Cited by
- 407
- References
- 23
- Citations by year
- 2026: 21 · 2025: 25 · 2024: 29 · 2023: 23 · 2022: 25 · 2021: 28 · 2020: 47 · 2019: 30 · 2018: 23 · 2017: 20 · 2016: 28 · 2015: 20 · 2014: 20 · 2013: 15 · 2012: 19
- FWCI
- 4.09
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biometrics (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Science Foundation
- National Institutes of Health
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Keywords
- change point detection, array comparative genomic hybridization, model selection, copy number alterations
- MeSH terms
- Bayes Theorem, Biometry, Cell Line, Computer Simulation, Humans, Models, Genetic, Monte Carlo Method, Nucleic Acid Hybridization, Genome, Oligonucleotide Array Sequence Analysis
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