A Hidden Markov Model to estimate population mixture and allelic copy-numbers in cancers using Affymetrix SNP arrays
作者： Philippe Lamy , Claus L Andersen , Lars Dyrskjot , Niels Torring , Carsten Wiuf
关键词: Genetics 、 SNP 、 Human genome 、 Allelic Imbalance 、 Biology 、 Population 、 Hidden Markov model 、 Markov chain 、 SNP array 、 Single-nucleotide polymorphism
摘要: Background Affymetrix SNP arrays can interrogate thousands of SNPs at the same time. This allows us to look genomic content cancer cells and investigate underlying events leading cancer. Genomic copy-numbers are today routinely derived from array data, but proposed algorithms for this task most often disregard genotype information available germline in paired germline-tumour samples. Including may deepen our understanding "true" biological situation e.g. by enabling analysis allele specific copy-numbers. Here we rely on matched samples have developed a Hidden Markov Model (HMM) estimate allelic copy-number changes tumour cells. Further with approach able proportion normal (mixture proportion).
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