chip artifact CORRECTion (caCORRECT): A Bioinformatics System for Quality Assurance of Genomics and Proteomics Array Data
Open Access
- 26 April 2007
- journal article
- Published by Springer Nature in Annals of Biomedical Engineering
- Vol. 35 (6) , 1068-1080
- https://doi.org/10.1007/s10439-007-9313-y
Abstract
Quality assurance of high throughput “-omics” data is a major concern for biomedical discovery and translational medicine, and is considered a top priority in bioinformatics and systems biology. Here, we report a web-based bioinformatics tool called caCORRECT for chip artifact detection, analysis, and CORRECTion, which removes systematic artifactual noises that are commonly observed in microarray gene expression data. Despite the development of major databases such as GEO arrayExpress, caArray, and the SMD to manage and distribute microarray data to the public, reproducibility has been questioned in many cases, including high-profile papers and datasets. Based on both archived and synthetic data, we have designed the caCORRECT to have several advanced features: (1) to uncover significant, correctable artifacts that affect reproducibility of experiments; (2) to improve the integrity and quality of public archives by removing artifacts; (3) to provide a universal quality score to aid users in their selection of suitable microarray data; and (4) to improve the true-positive rate of biomarker selection verified by test data. These features are expected to improve the reproducibility of Microarray study. caCORRECT is freely available at: http://caCORRECT.bme.gatech.edu.Keywords
This publication has 27 references indexed in Scilit:
- Quality Assessment for Short Oligonucleotide Microarray DataTechnometrics, 2008
- Transcriptional response to nitrosative stress in Saccharomyces cerevisiaeYeast, 2006
- The Stanford Microarray Database accommodates additional microarray platforms and data formatsNucleic Acids Research, 2004
- Identification and handling of artifactual gene expression profiles emerging in microarray hybridization experimentsNucleic Acids Research, 2004
- Effects of Atmospheric Ozone on Microarray Data QualityAnalytical Chemistry, 2003
- A comparison of normalization methods for high density oligonucleotide array data based on variance and biasBioinformatics, 2003
- The Stanford Microarray Database: data access and quality assessment toolsNucleic Acids Research, 2003
- Options available—from start to finish—for obtaining data from DNA microarrays IINature Genetics, 2002
- Fundamentals of experimental design for cDNA microarraysNature Genetics, 2002
- Gene-expression profiles predict survival of patients with lung adenocarcinomaNature Medicine, 2002