TY - JOUR
T1 - A very fast and accurate method for calling aberrations in array-CGH data
AU - Benelli, Matteo
AU - Marseglia, Giuseppina
AU - Nannetti, Genni
AU - Paravidino, Roberta
AU - Zara, Federico
AU - Bricarelli, Franca Dagna
AU - Torricelli, Francesca
AU - Magi, Alberto
PY - 2010/7
Y1 - 2010/7
N2 - 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.
AB - 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.
KW - array-CGH
KW - Calling procedure
UR - http://www.scopus.com/inward/record.url?scp=77956633483&partnerID=8YFLogxK
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U2 - 10.1093/biostatistics/kxq008
DO - 10.1093/biostatistics/kxq008
M3 - Article
C2 - 20207682
AN - SCOPUS:77956633483
VL - 11
SP - 515
EP - 518
JO - Biostatistics
JF - Biostatistics
SN - 1465-4644
IS - 3
ER -