A very fast and accurate method for calling aberrations in array-CGH data
| Autor: | Matteo Benelli, Giuseppina Marseglia, Franca Dagna Bricarelli, Genni Nannetti, Federico Zara, Roberta Paravidino, Alberto Magi, Francesca Torricelli |
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| Rok vydání: | 2010 |
| Předmět: |
Statistics and Probability
Comparative Genomic Hybridization Computer science business.industry Truncated normal distribution array-CGH Calling procedure Pattern recognition General Medicine Running time Identification (information) Workflow Gene chip analysis Computer Simulation Segmentation Artificial intelligence Statistics Probability and Uncertainty Probabilistic framework business Algorithms Oligonucleotide Array Sequence Analysis Comparative genomic hybridization |
| Zdroj: | Biostatistics. 11:515-518 |
| ISSN: | 1468-4357 1465-4644 |
| DOI: | 10.1093/biostatistics/kxq008 |
| Popis: | Array comparative genomic hybridization (aCGH) is a microarray technology that allows one to detect and map genomic alterations. The standard workflow of the aCGH data analysis consists of 2 steps: detecting the boundaries of the regions of changed copy number by means of a segmentation algorithm (break point identification) and then labeling each region as loss, neutral, or gain with a probabilistic framework (calling procedure). In this paper, we introduce a novel calling procedure based on a mixture of truncated normal distributions, named FastCall, that aims to give aberration probabilities to segmented aCGH data in a very fast and accurate way. Both on synthetic and real aCGH data, FastCall obtains excellent performances in terms of classification accuracy and running time. |
| Databáze: | OpenAIRE |
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