نتایج جستجو برای: comparative genomic hybridization
تعداد نتایج: 397000 فیلتر نتایج به سال:
Array-based comparative genomic hybridization is a high resolution method for measuring chromosomal copy number changes. Here we present a validated protocol using in-house spotted oligonucleotide libraries for array comparative genomic hybridization (CGH). This oligo array CGH platform yields reproducible results and is capable of detecting single copy gains, multi-copy amplifications as well ...
We read with interest the recent review by Santiago Munné entitled, “Preimplantation Genetic Diagnosis for Aneuploidy and Translocations Using Array Comparative Genomic Hybridization” (1). As part of the review of array comparative genome hybridization (aCGH), the author provides additional information on other 24-chromosome preimplantation genetic diagnosis/screening (PGD/PGS) techniques. As a...
We propose a method for high-dimensional curve clustering in the presence of interindividual variability. Curve clustering has longly been studied especially using splines to account for functional random effects. However, splines are not appropriate when dealing with high-dimensional data and can not be used to model irregular curves such as peak-like data. Our method is based on a wavelet dec...
NEW TECHNOLOGIES THAT ALlow scientists to rapidly analyze a person’s genome for potentially deleterious variations are now being used by at least 1 company and an academic medical center for prenatal testing, igniting a debate among scientists about the clinical value and ethical implications of the procedure. As data emerge from early clinical studies that use microarray comparative genomic hy...
Microarray-based comparative genomic hybridization (array-CGH) has emerged as a revolutionary platform, enabling the high-resolution detection of DNA copy number aberrations. In this article we outline the use and limitations of genomic clones, cDNA clones and PCR products as targets for genomic microarray construction. Furthermore, the applications and future aspects of these arrays for DNA co...
Comparative genome hybridization (CGH) to DNA microarrays (array CGH) is a technique capable of detecting deletions and duplications in genomes at high resolution. However, array CGH studies of the human genome noting false negative and false positive results using large insert clones as probes have raised important concerns regarding the suitability of this approach for clinical diagnostic app...
Pathological copy number variants (CNVs) and point mutations are major genetic causes of hundreds of disorders. Comparative genomic hybridization (CGH) also known as chromosomal microarray analysis (CMA) is the best available tool to detect copy number variations in chromosomal make up. We have optimized several different protocols and introduce a high-throughput approach to perform a cost-effe...
Array comparative genomic hybridization (array CGH) is a technique for assaying the copy number status of cancer genomes. The widespread use of this technology has lead to a rapid accumulation of high throughput data, which in turn has prompted the development of computational strategies for the analysis of array CGH data. Here we explain the principles behind array image processing, data visua...
In the analysis of data generated by change-point processes, one critical challenge is to determine the number of change-points. The classic Bayes information criterion (BIC) statistic does not work well here because of irregularities in the likelihood function. By asymptotic approximation of the Bayes factor, we derive a modified BIC for the model of Brownian motion with changing drift. The mo...
Regularized generalized canonical correlation analysis (RGCCA) is a generalization of regularized canonical correlation analysis to 3 or more sets of variables. RGCCA is a component-based approach which aims to study the relationships between several sets of variables. The quality and interpretability of the RGCCA components are likely to be affected by the usefulness and relevance of the varia...
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