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Identification of nutrient partitioning genes participating in rice grain filling by singular value decomposition (SVD) of genome expression data
BACKGROUND: In order to identify rice genes involved in nutrient partitioning, microarray experiments have been done to quantify genomic scale gene expression. Genes involved in nutrient partitioning, specifically grain filling, will be used to identify other co-regulated genes, and DNA binding prot...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2003
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC169189/ https://www.ncbi.nlm.nih.gov/pubmed/12854976 http://dx.doi.org/10.1186/1471-2164-4-26 |
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author | Anderson, Abraham Hudson, Matthew Chen, Wenqiong Zhu, Tong |
author_facet | Anderson, Abraham Hudson, Matthew Chen, Wenqiong Zhu, Tong |
author_sort | Anderson, Abraham |
collection | PubMed |
description | BACKGROUND: In order to identify rice genes involved in nutrient partitioning, microarray experiments have been done to quantify genomic scale gene expression. Genes involved in nutrient partitioning, specifically grain filling, will be used to identify other co-regulated genes, and DNA binding proteins. Proper identification of the initial set of bait genes used for further investigation is critical. Hierarchical clustering is useful for grouping genes with similar expression profiles, but decreases in utility as data complexity and systematic noise increases. Also, its rigid classification of genes is not consistent with our belief that some genes exhibit multifaceted, context dependent regulation. RESULTS: Singular value decomposition (SVD) of microarray data was investigated as a method to complement current techniques for gene expression pattern recognition. SVD's usefulness, in finding likely participants in grain filling, was measured by comparison with results obtained previously via clustering. 84 percent of these known grain-filling genes were re-identified after detailed SVD analysis. An additional set of 28 genes exhibited a stronger grain-filling pattern than those grain-filling genes that were unselected. They also had upstream sequence containing motifs over-represented among grain filling genes. CONCLUSIONS: The pattern-based perspective that SVD provides complements to widely used clustering methods. The singular vectors provide information about patterns that exist in the data. Other aspects of the decomposition indicate the extent to which a gene exhibits a pattern similar to those provided by the singular vectors. Thus, once a set of interesting patterns has been identified, genes can be ranked by their relationship with said patterns. |
format | Text |
id | pubmed-169189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2003 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-1691892003-08-06 Identification of nutrient partitioning genes participating in rice grain filling by singular value decomposition (SVD) of genome expression data Anderson, Abraham Hudson, Matthew Chen, Wenqiong Zhu, Tong BMC Genomics Research Article BACKGROUND: In order to identify rice genes involved in nutrient partitioning, microarray experiments have been done to quantify genomic scale gene expression. Genes involved in nutrient partitioning, specifically grain filling, will be used to identify other co-regulated genes, and DNA binding proteins. Proper identification of the initial set of bait genes used for further investigation is critical. Hierarchical clustering is useful for grouping genes with similar expression profiles, but decreases in utility as data complexity and systematic noise increases. Also, its rigid classification of genes is not consistent with our belief that some genes exhibit multifaceted, context dependent regulation. RESULTS: Singular value decomposition (SVD) of microarray data was investigated as a method to complement current techniques for gene expression pattern recognition. SVD's usefulness, in finding likely participants in grain filling, was measured by comparison with results obtained previously via clustering. 84 percent of these known grain-filling genes were re-identified after detailed SVD analysis. An additional set of 28 genes exhibited a stronger grain-filling pattern than those grain-filling genes that were unselected. They also had upstream sequence containing motifs over-represented among grain filling genes. CONCLUSIONS: The pattern-based perspective that SVD provides complements to widely used clustering methods. The singular vectors provide information about patterns that exist in the data. Other aspects of the decomposition indicate the extent to which a gene exhibits a pattern similar to those provided by the singular vectors. Thus, once a set of interesting patterns has been identified, genes can be ranked by their relationship with said patterns. BioMed Central 2003-07-10 /pmc/articles/PMC169189/ /pubmed/12854976 http://dx.doi.org/10.1186/1471-2164-4-26 Text en Copyright © 2003 Anderson et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL. |
spellingShingle | Research Article Anderson, Abraham Hudson, Matthew Chen, Wenqiong Zhu, Tong Identification of nutrient partitioning genes participating in rice grain filling by singular value decomposition (SVD) of genome expression data |
title | Identification of nutrient partitioning genes participating in rice grain filling by singular value decomposition (SVD) of genome expression data |
title_full | Identification of nutrient partitioning genes participating in rice grain filling by singular value decomposition (SVD) of genome expression data |
title_fullStr | Identification of nutrient partitioning genes participating in rice grain filling by singular value decomposition (SVD) of genome expression data |
title_full_unstemmed | Identification of nutrient partitioning genes participating in rice grain filling by singular value decomposition (SVD) of genome expression data |
title_short | Identification of nutrient partitioning genes participating in rice grain filling by singular value decomposition (SVD) of genome expression data |
title_sort | identification of nutrient partitioning genes participating in rice grain filling by singular value decomposition (svd) of genome expression data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC169189/ https://www.ncbi.nlm.nih.gov/pubmed/12854976 http://dx.doi.org/10.1186/1471-2164-4-26 |
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