Distance-based clustering of CGH data

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Distance-based clustering of CGH data

MOTIVATION We consider the problem of clustering a population of Comparative Genomic Hybridization (CGH) data samples. The goal is to develop a systematic way of placing patients with similar CGH imbalance profiles into the same cluster. Our expectation is that patients with the same cancer types will generally belong to the same cluster as their underlying CGH profiles will be similar. RESUL...

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Model-based clustering of array CGH data

MOTIVATION Analysis of array comparative genomic hybridization (aCGH) data for recurrent DNA copy number alterations from a cohort of patients can yield distinct sets of molecular signatures or profiles. This can be due to the presence of heterogeneous cancer subtypes within a supposedly homogeneous population. RESULTS We propose a novel statistical method for automatically detecting such sub...

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Markers improve clustering of CGH data

MOTIVATION We consider the problem of clustering a population of Comparative Genomic Hybridization (CGH) data samples using similarity based clustering methods. A key requirement for clustering is to avoid using the noisy aberrations in the CGH samples. RESULTS We develop a dynamic programming algorithm to identify a small set of important genomic intervals called markers. The advantage of us...

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Weighted clustering of called array CGH data

Array comparative genomic hybridization (aCGH) is a laboratory technique to measure chromosomal copy number changes. A clear biological interpretation of the measurements is obtained by mapping these onto an ordinal scale with categories loss/normal/gain of a copy. The pattern of gains and losses harbors a level of tumor specificity. Here, we present WECCA (weighted clustering of called aCGH da...

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Weighted clustering of called array CGH data.

Array comparative genomic hybridization (aCGH) is a laboratory technique to measure chromosomal copy number changes. A clear biological interpretation of the measurements is obtained by mapping these onto an ordinal scale with categories loss/normal/gain of a copy. The pattern of gains and losses harbors a level of tumor specificity. Here, we present WECCA (weighted clustering of called aCGH da...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2006

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/btl185