Efficiency of hybrid normalization of microarray gene expression: A simulation study

Mehdi Pirooznia; Youping Deng

doi:10.1109/AINAW.2007.164

Efficiency of hybrid normalization of microarray gene expression: A simulation study

Mehdi Pirooznia, Youping Deng

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Microarray experiment's data contain errors, from various sources. The process of identifying and adjusting of systematic variation in intensities between samples on the same slide is known as normalization. We implemented a java application with graphical user interface that allows easy evaluation of errors and the role of hybrid normalization methods to remove the systematic errors from the experiment's data. We calculated true hybridization intensity then applied different additive and multiplicative errors and computed the normalized intensity logged ratio using background subtraction, self-normalization method and dye-flip technique. Results show the efficiency of hybrid normalization method in order to remove error rates from the intensity values.

Original language	English (US)
Title of host publication	Proceedings - 21st International Conference on Advanced Information Networking and Applications Workshops/Symposia, AINAW'07
Pages	739-744
Number of pages	6
Volume	2
DOIs	https://doi.org/10.1109/AINAW.2007.164
State	Published - 2007
Externally published	Yes
Event	21st International Conference on Advanced Information Networking and ApplicationsWorkshops/Symposia, AINAW'07 - Niagara Falls, ON, Canada Duration: May 21 2007 → May 23 2007

Other

Other	21st International Conference on Advanced Information Networking and ApplicationsWorkshops/Symposia, AINAW'07
Country/Territory	Canada
City	Niagara Falls, ON
Period	5/21/07 → 5/23/07

ASJC Scopus subject areas

Computer Networks and Communications
Software
Mathematics(all)

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10.1109/AINAW.2007.164

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Pirooznia, M & Deng, Y 2007, Efficiency of hybrid normalization of microarray gene expression: A simulation study. in Proceedings - 21st International Conference on Advanced Information Networking and Applications Workshops/Symposia, AINAW'07. vol. 2, 4221146, pp. 739-744, 21st International Conference on Advanced Information Networking and ApplicationsWorkshops/Symposia, AINAW'07, Niagara Falls, ON, Canada, 5/21/07. https://doi.org/10.1109/AINAW.2007.164

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abstract = "Microarray experiment's data contain errors, from various sources. The process of identifying and adjusting of systematic variation in intensities between samples on the same slide is known as normalization. We implemented a java application with graphical user interface that allows easy evaluation of errors and the role of hybrid normalization methods to remove the systematic errors from the experiment's data. We calculated true hybridization intensity then applied different additive and multiplicative errors and computed the normalized intensity logged ratio using background subtraction, self-normalization method and dye-flip technique. Results show the efficiency of hybrid normalization method in order to remove error rates from the intensity values.",

author = "Mehdi Pirooznia and Youping Deng",

year = "2007",

doi = "10.1109/AINAW.2007.164",

language = "English (US)",

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booktitle = "Proceedings - 21st International Conference on Advanced Information Networking and Applications Workshops/Symposia, AINAW'07",

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PY - 2007

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N2 - Microarray experiment's data contain errors, from various sources. The process of identifying and adjusting of systematic variation in intensities between samples on the same slide is known as normalization. We implemented a java application with graphical user interface that allows easy evaluation of errors and the role of hybrid normalization methods to remove the systematic errors from the experiment's data. We calculated true hybridization intensity then applied different additive and multiplicative errors and computed the normalized intensity logged ratio using background subtraction, self-normalization method and dye-flip technique. Results show the efficiency of hybrid normalization method in order to remove error rates from the intensity values.

AB - Microarray experiment's data contain errors, from various sources. The process of identifying and adjusting of systematic variation in intensities between samples on the same slide is known as normalization. We implemented a java application with graphical user interface that allows easy evaluation of errors and the role of hybrid normalization methods to remove the systematic errors from the experiment's data. We calculated true hybridization intensity then applied different additive and multiplicative errors and computed the normalized intensity logged ratio using background subtraction, self-normalization method and dye-flip technique. Results show the efficiency of hybrid normalization method in order to remove error rates from the intensity values.

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SN - 9780769528472

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BT - Proceedings - 21st International Conference on Advanced Information Networking and Applications Workshops/Symposia, AINAW'07

Y2 - 21 May 2007 through 23 May 2007

ER -

Efficiency of hybrid normalization of microarray gene expression: A simulation study

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