Modelling the background correction in microarray data analysis

Risultato della ricerca: Other

Abstract

Microarray technology has been adopted in many areas of biomedical research for quantitative and highly parallel measurements of gene expressions.In this field, the high density oligonucleotide microarray technology is the mostused platform; in this platform oligonucleotides of 25 base pairs are used as probegenes. Two types of probes are considered: perfect match (PM) and mismatch (MM)probes. In theory, MM probes are used to quantify and remove two types of error:optical noise and non specific binding. The correction of these two types of error isknown as background correction. Preprocessing is an essential step of the analysisin which the intensity, read from each probe, is manipulated in order to obtain anexpression measure for each gene. In this paper, we introduce a new method for thebackground correction by using a calibration approach based on a generalized linearmixed model (GLMM).
Lingua originaleUndefined/Unknown
Pagine1593-1600
Stato di pubblicazionePublished - 2006

Cita questo