Normalization of cDNA microarray data.

cDNA Microarray Data Normalization

Normalization of cDNA Microarray Data By Using Neural Networks

In microarray experiments, there are a variety of systematic errors to affect the measured gene expression levels. Although a number of algorithms were proposed for the normalization of different type of cDNA microarray data, they have encountered many difficulties due to the complex nonlinear sources of systematic error. In this case, a nonlinear normalization method is of great potential to d...

Package ‘ TwslmSpikeWeight ’ April 17 , 2009

April 17, 2009 Version 1.0.1 Date 2006-01-17 Maintainer Deli Wang Author Deli Wang, Jian Huang Depends splines Title Systematic approaches using TW-SLM for incorporating control spots and data quality information to improve normalization of cDNA microarray data. Description TwslmSpikeWeight is for normalization of cDNA microarray data with the two-way semilinear model(TW...

arrayMagic: two-colour cDNA microarray quality control and preprocessing

Summary: arrayMagic is a software package for quality control and preprocessing of two-colour cDNA microarray data. The automated analysis pipeline comprises data import, normalization, replica merging, quality diagnostics and data export. The script-based processing combines reproducibility and flexibility at high-throughput and provides quality-assured and preprocessed microarray data to high...

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...

A Two-Way Semi-Linear Model for Normalization and Significant Analysis of cDNA Microarray Data

A basic question in analyzing cDNA microarray data is normalization. The purpose of normalization is to remove systematic bias in the observed expression values by establishing a normalization curve across the whole dynamic range. A proper normalization procedure ensures that the normalized intensity ratios provide meaningful measures of relative expression levels. We propose a two-way semi-lin...