Characterization and Normalization Algorithms for High-Density Oligonucleotide Gene Expression Array Data
- 详细技术说明
- Researchers at the University of California have developed an algorithm and methodology that more accurately reflects normalized data between arrays than methods that are currently in use.
- *Abstract
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None
- *IP Issue Date
- May 27, 2003
- *Principal Investigation
-
Name: Cheng Li
Department:
Name: Wing Wong
Department:
- 附加资料
- Patent Number: US6571005B1
Application Number: US2000556497A
Inventor: Li, Cheng | Wong, Wing Hung
Priority Date: 21 Apr 2000
Priority Number: US6571005B1
Application Date: 21 Apr 2000
Publication Date: 27 May 2003
IPC Current: C12Q000100 | G06F001920 | G06K000900 | G06T000700
US Class: 382133
Assignee Applicant: The Regents of the University of California
Title: Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data
Usefulness: Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data
Summary: M1 is useful for determining a characteristic intensity of or a value for, a feature in image data generated by scanning a microarray probe. M2 is useful for relating a first expression array of probes to a second expression array of probes (claimed). The methods are used for analyzing a gene probe microarray and image data produced by the microarrays.
Novelty: Determining characteristic intensity of feature in image data generated by scanning microarray probe, comprising identifying set of pixels representing feature, determining variation statistic value, choosing pixels from set
- 主要类别
- 生物医学
- 细分类别
- DNA /基因工程
- 申请号码
- 6571005
- 其他
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BACKGROUND
Monitoring gene expression using high-density microarrays is a frequently-used technique in the study of cell functions and the associated biochemical pathways, candidate gene identification, cellular response to drug compounds, and classification of disease states. Because many important decisions as to whether a gene should be pursued as a candidate for a particular biological system under study are based on determined expression ratios as well as on determined differential expression, processes that provide for more accurate estimates of these derived statistics can be valuable to users of oligonucleotide array technology.
Conventional normalization methods include 1) linear normalization and nonlinear regression, and 2) methods using housekeeping genes or staggered spike-in controls. These methods have drawbacks, however. The linear normalization technique does not account well for nonlinear relations. Non-linear regression can be inadequate if the expression profiles of the various arrays vary greatly from each other. Finally, many of the genes conventionally used as housekeeping genes have ranges of differential expression similar to other genes whose differential expression patterns are deemed biologically relevant to the system under study.
Tech ID/UC Case
10177/2000-267-0
Related Cases
2000-267-0
- 国家/地区
- 美国
