Spatial analysis of cDNA microarray experiments

By:

Burgueño, J

Contributor(s):

Material type: Article

ArticleLanguage: English Publication details: USA : CSSA : Wiley, 2005.ISSN:

1435-0653 (Online)

Subject(s):

Online resources:

Access only for CIMMYT Staff

In: Crop Science v. 45, no. 2, p. 748-757630716Summary: Microarray experiments allow RNA level measurements for many genes in multiple samples. However, mining the biological information from the large sets of data generated by microarrays requires the use of appropriate statistical methods to adjust the observed values for experimentally introduced variability (normalization process) before testing differences among samples. Normalization of microarray experiments is a critical step for reducing false positives and false negatives. This paper explores the normalization of cDNA microarray experiments by a method that uses the blank spot intensity values to make spatial adjustment (SA) of both foreground and background DNA spot intensity values, by fitting an autoregressive mixed linear model through the residual maximum likelihood (REML) methodology in the direction of the rows and the columns of the microarray. Application of this spatial normalization to three cDNA array experiments serves as a case study to validate the SA. Results show that the spatial analysis allows selection of candidate genes with lesser numbers of false positive and false negative genes.

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Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode	Item holds
Article	CIMMYT Knowledge Center: John Woolston Library	CIMMYT Staff Publications Collection	CIS-4366 (Browse shelf(Opens below))	1	Available		630716

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Peer-review: Yes - Open Access: Yes|http://science.thomsonreuters.com/cgi-bin/jrnlst/jlresults.cgi?PC=MASTER&ISSN=0011-183X

Microarray experiments allow RNA level measurements for many genes in multiple samples. However, mining the biological information from the large sets of data generated by microarrays requires the use of appropriate statistical methods to adjust the observed values for experimentally introduced variability (normalization process) before testing differences among samples. Normalization of microarray experiments is a critical step for reducing false positives and false negatives. This paper explores the normalization of cDNA microarray experiments by a method that uses the blank spot intensity values to make spatial adjustment (SA) of both foreground and background DNA spot intensity values, by fitting an autoregressive mixed linear model through the residual maximum likelihood (REML) methodology in the direction of the rows and the columns of the microarray. Application of this spatial normalization to three cDNA array experiments serves as a case study to validate the SA. Results show that the spatial analysis allows selection of candidate genes with lesser numbers of false positive and false negative genes.

Genetic Resources Program

Text in English

0503|Crop Science Society of America (CSSA)|AL-ABC Program

INT3239|CCJL01

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Knowledge Center Catalog

Spatial analysis of cDNA microarray experiments

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International Maize and Wheat Improvement Center (CIMMYT) © Copyright 2021.
Carretera México-Veracruz. Km. 45, El Batán, Texcoco, México, C.P. 56237.
If you have any question, please contact us at
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Knowledge Center Catalog

Spatial analysis of cDNA microarray experiments

Browsing CIMMYT Knowledge Center: John Woolston Library shelves, Collection: CIMMYT Staff Publications Collection Close shelf browser (Hides shelf browser)

International Maize and Wheat Improvement Center (CIMMYT) © Copyright 2021. Carretera México-Veracruz. Km. 45, El Batán, Texcoco, México, C.P. 56237. If you have any question, please contact us at CIMMYT-Knowledge-Center@cgiar.org

International Maize and Wheat Improvement Center (CIMMYT) © Copyright 2021.
Carretera México-Veracruz. Km. 45, El Batán, Texcoco, México, C.P. 56237.
If you have any question, please contact us at
CIMMYT-Knowledge-Center@cgiar.org