A very fast and accurate method for calling aberrations in array-CGH data

Matteo Benelli, Giuseppina Marseglia, Genni Nannetti, Roberta Paravidino, Federico Zara, Franca Dagna Bricarelli, Francesca Torricelli, Alberto Magi

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)515-518
Number of pages4
Issue number3
Publication statusPublished - Jul 2010


  • array-CGH
  • Calling procedure

ASJC Scopus subject areas

  • Medicine(all)
  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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