The study of a metabolic pathway is focused on a limited number of genes unsuited for normalizing raw expression data, nevertheless a large number of (spike) controls and replicates may be printed within slide. We develop a linear additive mixed effect model to remove dye and spatial biases using spike controls. We adapt the iterated weighted least squares algorithm to perform model selection and to obtain point estimates of model parameters. Actual data from a very noisy calibration slide have been successfully normalized following our model.
An additive model to normalize spotted arrays using spike controls / F. M. STEFANINI; M. MASCHERINI ; M. BRANDI ; C. MAVILIA. - STAMPA. - Atti del Congresso:(2007), pp. 101-104. (Intervento presentato al convegno SIB2007 Congresso Nazionale della Società Italiana di Biometria tenutosi a Marina di Massa nel Giugno 2007).
An additive model to normalize spotted arrays using spike controls
STEFANINI, FEDERICO MATTIA;BRANDI, MARIA LUISA;MAVILIA, CARMELO
2007
Abstract
The study of a metabolic pathway is focused on a limited number of genes unsuited for normalizing raw expression data, nevertheless a large number of (spike) controls and replicates may be printed within slide. We develop a linear additive mixed effect model to remove dye and spatial biases using spike controls. We adapt the iterated weighted least squares algorithm to perform model selection and to obtain point estimates of model parameters. Actual data from a very noisy calibration slide have been successfully normalized following our model.
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