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Accurate estimation of homologue-specific DNA concentration-ratios in cancer samples allows long-range haplotyping Nature Precedings
Scott L. Carter; Matthew Meyerson; Gad Getz.
Interpretation of allelic copy measurements at polymorphic markers in cancer samples presents distinctive challenges and opportunities. Due to frequent gross chromosomal alterations occurring in cancer (aneuploidy), many genomic regions are present at homologous-allele imbalance. Within such regions, the unequal contribution of alleles at heterozygous markers allows for direct phasing of the haplotype derived from each individual parent. In addition, genome-wide estimates of homologue specific copy- ratios (HSCRs) are important for interpretation of the cancer genome in terms of fixed integral copy-numbers. We describe HAPSEG, a probabilistic method to interpret bi- allelic marker data in cancer samples. HAPSEG operates by partitioning the genome into...
Tipo: Manuscript Palavras-chave: Cancer; Genetics & Genomics; Bioinformatics.
Ano: 2011 URL: http://precedings.nature.com/documents/6494/version/1
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High-order chromatin architecture determines the landscape of chromosomal alterations in cancer Nature Precedings
Geoffrey Fudenberg; Gad Getz; Matthew Meyerson; Leonid Mirny.
The rapid growth of cancer genome structural information provides an opportunity for a better understanding of the mutational mechanisms of genomic alterations in cancer and the forces of selection that act upon them. Here we test the evidence for two major forces, spatial chromosome structure and purifying (or negative) selection, that shape the landscape of somatic copy-number alterations (SCNAs) in cancer. Using a maximum likelihood framework we compare SCNA maps and three-dimensional genome architecture as determined by genome-wide chromosome conformation capture (HiC) and described by the proposed fractal-globule (FG) model. This analysis provides evidence that the distribution of chromosomal alterations in cancer is spatially related to...
Tipo: Manuscript Palavras-chave: Cancer; Genetics & Genomics; Bioinformatics.
Ano: 2011 URL: http://precedings.nature.com/documents/6356/version/1
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