Non-linear normalization and background correction in one-channel cDNA microarray studies

Non-linear Normalization and Background Correction in One-channel CDNA Microarray Studies

MOTIVATION Data from one-channel cDNA microarray studies may exhibit poor reproducibility due to spatial heterogeneity, non-linear array-to-array variation and problems in correcting for background. Uncorrected, these phenomena can give rise to misleading conclusions. RESULTS Spatial heterogeneity may be corrected using two-dimensional loess smoothing (Colantuoni et al., 2002). Non-linear bet...

cDNA Microarray Data Normalization

Normalization of cDNA microarray data.

Normalization means to adjust microarray data for effects which arise from variation in the technology rather than from biological differences between the RNA samples or between the printed probes. This paper describes normalization methods based on the fact that dye balance typically varies with spot intensity and with spatial position on the array. Print-tip loess normalization provides a wel...

New Normalization Methods for CDNA Microarray Data

MOTIVATION The focus of this paper is on two new normalization methods for cDNA microarrays. After the image analysis has been performed on a microarray and before differentially expressed genes can be detected, some form of normalization must be applied to the microarrays. Normalization removes biases towards one or other of the fluorescent dyes used to label each mRNA sample allowing for prop...

Identification and Normalization of Plate Effects in Cdna Microarray Data

Introducing a new way of visualizing cDNA microarray data we have identified a new type of systematic variation, which we refer to as plate effects. We believe that plate effects are due to non-biological differences in the cDNA clones products spotted onto the microarray slides. By comparing the consistency of all replicates (both within and between slides) after performing 42 different normal...