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Title:
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CONTINUOUS-TIME HIDDEN MARKOV MODELS FOR THE COPY NUMBER ANALYSIS OF GENOTYPING ARRAYS |
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Author(s):
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Matthew Kowgier , Rafal Kustra |
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ISBN:
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978-972-8924-88-1 |
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Editors:
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Ajith P. Abraham |
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Year:
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2009 |
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Edition:
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Single |
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Keywords:
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Hidden Markov Models; EM algorithm; copy number variation; HapMap; genotyping arrays |
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Type:
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Full Paper |
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First Page:
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43 |
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Last Page:
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49 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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We present a novel Hidden Markov Model for detecting copy number variations (CNV) from genotyping arrays. Our
model is a novel application of HMM to inferring CNVs from genotyping arrays: it assumes a continuous time
framework and is informed by prior findings from previously analysed real data. This framework is also more realistic
than discrete-time models which are currently used since the underlying genomic sequence is few hundred times denser
than the array data. We show how to estimate the model parameters using a training data of normal samples whose CNV
regions have been confirmed, and present results from applying the model to a set of HapMap samples containing
aberrant SNPs. |
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