title: GPHMM: an integrated hidden Markov model for identification of copy number alteration and loss of heterozygosity in complex tumor samples using whole genome SNP arrays.
abstract: There is an increasing interest in using single nucleotide polymorphism (SNP) genotyping arrays for profiling chromosomal rearrangements in tumors, as they allow simultaneous detection of copy number and loss of heterozygosity with high resolution. Critical issues such as signal baseline shift due to aneuploidy, normal cell contamination, and the presence of GC content bias have been reported to dramatically alter SNP array signals and complicate accurate identification of aberrations in cancer genomes. To address these issues, we propose a novel Global Parameter Hidden Markov Model (GPHMM) to unravel tangled genotyping data generated from tumor samples. In contrast to other HMM methods, a distinct feature of GPHMM is that the issues mentioned above are quantitatively modeled by global parameters and integrated within the statistical framework. We developed an efficient EM algorithm for parameter estimation. We evaluated performance on three data sets and show that GPHMM can correctly identify chromosomal aberrations in tumor samples containing as few as 10% cancer cells. Furthermore, we demonstrated that the estimation of global parameters in GPHMM provides information about the biological characteristics of tumor samples and the quality of genotyping signal from SNP array experiments, which is helpful for data quality control and outlier detection in cohort studies.
authors.affiliation: Department of Electronic Science and Technology, University of Science and Technology of China.
authors.forename: Ao
authors.initials: A
authors.lastname: Li
authors.forename: Zongzhi
authors.initials: Z
authors.lastname: Liu
authors.forename: Kimberly
authors.initials: K
authors.lastname: Lezon-Geyda
authors.forename: Sudipa
authors.initials: S
authors.lastname: Sarkar
authors.forename: Donald
authors.initials: D
authors.lastname: Lannin
authors.forename: Vincent
authors.initials: V
authors.lastname: Schulz
authors.forename: Ian
authors.initials: I
authors.lastname: Krop
authors.forename: Eric
authors.initials: E
authors.lastname: Winer
authors.forename: Lyndsay
authors.initials: L
authors.lastname: Harris
authors.forename: David
authors.initials: D
authors.lastname: Tuck
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000235:genetics; D045744:Cell Line, Tumor; D056915:DNA Copy Number Variations; D005260:Female; D018628:Gene Dosage; D018734:Genes, erbB-2; D015894:Genome, Human; D006801:Humans; D019656:Loss of Heterozygosity; D008390:Markov Chains; D009369:Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D020641:Polymorphism, Single Nucleotide