Probe-specific mixed-model approach to detect copy number differences using multiplex ligation-dependent probe amplification (MLPA).
BACKGROUND
MLPA method is a potentially useful semi-quantitative method to detect copy number alterations in targeted regions. In this paper, we propose a method for the normalization procedure based on a non-linear mixed-model, as well as a new approach for determining the statistical significance of altered probes based on linear mixed-model. This method establishes a threshold by using different tolerance intervals that accommodates the specific random error variability observed in each test sample.


RESULTS
Through simulation studies we have shown that our proposed method outperforms two existing methods that are based on simple threshold rules or iterative regression. We have illustrated the method using a controlled MLPA assay in which targeted regions are variable in copy number in individuals suffering from different disorders such as Prader-Willi, DiGeorge or Autism showing the best performace.


CONCLUSIONS
Using the proposed mixed-model, we are able to determine thresholds to decide whether a region is altered. These threholds are specific for each individual, incorporating experimental variability, resulting in improved sensitivity and specificity as the examples with real data have revealed.
Center for research in environmental epidemiology (CREAL), Barcelona, Spain. jrgonzalez@imim.es
Juan R
JR
González
Josep L
JL
Carrasco
Lluís
L
Armengol
Sergi
S
Villatoro
Lluís
L
Jover
Yutaka
Y
Yasui
Xavier
X
Estivill
D001321:Autistic Disorder / Q000235:genetics; D001943:Breast Neoplasms / Q000235:genetics; D016001:Confidence Intervals; D015342:DNA Probes / Q000032:analysis; D004062:DiGeorge Syndrome / Q000235:genetics; D018628:Gene Dosage; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease / Q000453:epidemiology; D014644:Genetic Variation; D006801:Humans; D016014:Linear Models; D015336:Molecular Probe Techniques / Q000706:statistics & numerical data; D016133:Polymerase Chain Reaction; D011218:Prader-Willi Syndrome / Q000235:genetics; D011237:Predictive Value of Tests; D012015:Reference Standards; D012016:Reference Values; D016037:Single-Blind Method; D013269:Stochastic Processes
D015342:DNA Probes; D005819:Genetic Markers