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Application of a correlation correction factor in a microarray cross-platform reproducibility study
- Source :
- BMC Bioinformatics, BMC Bioinformatics, Vol 8, Iss 1, p 447 (2007)
- Publication Year :
- 2007
- Publisher :
- Springer Science and Business Media LLC, 2007.
-
Abstract
- Background Recent research examining cross-platform correlation of gene expression intensities has yielded mixed results. In this study, we demonstrate use of a correction factor for estimating cross-platform correlations. Results In this paper, three technical replicate microarrays were hybridized to each of three platforms. The three platforms were then analyzed to assess both intra- and cross-platform reproducibility. We present various methods for examining intra-platform reproducibility. We also examine cross-platform reproducibility using Pearson's correlation. Additionally, we previously developed a correction factor for Pearson's correlation which is applicable when X and Y are measured with error. Herein we demonstrate that correcting for measurement error by estimating the "disattenuated" correlation substantially improves cross-platform correlations. Conclusion When estimating cross-platform correlation, it is essential to thoroughly evaluate intra-platform reproducibility as a first step. In addition, since measurement error is present in microarray gene expression data, methods to correct for attenuation are useful in decreasing the bias in cross-platform correlation estimates.
- Subjects :
- Computer science
Statistics as Topic
lcsh:Computer applications to medicine. Medical informatics
computer.software_genre
Biochemistry
Correlation
Structural Biology
Calibration
Humans
Microarray databases
lcsh:QH301-705.5
Molecular Biology
Reproducibility
Observational error
business.industry
Gene Expression Profiling
Applied Mathematics
Pattern recognition
Microarray Analysis
Computer Science Applications
Gene expression profiling
lcsh:Biology (General)
Gene chip analysis
lcsh:R858-859.7
Data mining
Artificial intelligence
business
computer
Research Article
Subjects
Details
- ISSN :
- 14712105
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- BMC Bioinformatics
- Accession number :
- edsair.doi.dedup.....d82d52b731f0a9a2d00cbe43756d7741