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A reference database for tumor-related genes co-expressed with interleukin-8 using genome-scale in silico analysis.

ABSTRACT: BACKGROUND:The EST database provides a rich resource for gene discovery and in silico expression analysis. We report a novel computational approach to identify co-expressed genes using EST database, and its application to IL-8. RESULTS:IL-8 is represented in 53 dbEST cDNA libraries. We calculated the frequency of occurrence of all the genes represented in these cDNA libraries, and ranked the candidates based on a Z-score. Additional analysis suggests that most IL-8 related genes are differentially expressed between non-tumor and tumor tissues. To focus on IL-8's function in tumor tissues, we further analyzed and ranked the genes in 16 IL-8 related tumor libraries. CONCLUSIONS:This method generated a reference database for genes co-expressed with IL-8 and could facilitate further characterization of functional association among genes.

SUBMITTER: Benbow L

PROVIDER: S-EPMC131052 | biostudies-literature | 2002 Oct

REPOSITORIES: biostudies-literature

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A reference database for tumor-related genes co-expressed with interleukin-8 using genome-scale in silico analysis.

Benbow Lawrence L Wang Lynn L Laverty Maureen M Liu Suxing S Qiu Ping P Bond Richard W RW Gustafson Eric E Hedrick Joseph A JA Kostich Mitchell M Greene Jonathan R JR Wang Luquan L

BMC genomics 20021011 1

<h4>Background</h4>The EST database provides a rich resource for gene discovery and in silico expression analysis. We report a novel computational approach to identify co-expressed genes using EST database, and its application to IL-8.<h4>Results</h4>IL-8 is represented in 53 dbEST cDNA libraries. We calculated the frequency of occurrence of all the genes represented in these cDNA libraries, and ranked the candidates based on a Z-score. Additional analysis suggests that most IL-8 related genes a ...[more]

PMID: 12377104

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Project description:Gene co-expression, the similarity of gene expression profiles under various experimental conditions, has been used as an indicator of functional relationships between genes, and many co-expression databases have been developed for predicting gene functions. These databases usually provide users with a co-expression network and a list of strongly co-expressed genes for a query gene. Several of these databases also provide functional information on a set of strongly co-expressed genes (i.e., provide biological processes and pathways that are enriched in these strongly co-expressed genes), which is generally analyzed via over-representation analysis (ORA). A limitation of this approach may be that users can predict gene functions only based on the strongly co-expressed genes.In this study, we developed a new co-expression database that enables users to predict the function of tomato genes from the results of functional enrichment analyses of co-expressed genes while considering the genes that are not strongly co-expressed. To achieve this, we used the ORA approach with several thresholds to select co-expressed genes, and performed gene set enrichment analysis (GSEA) applied to a ranked list of genes ordered by the co-expression degree. We found that internal correlation in pathways affected the significance levels of the enrichment analyses. Therefore, we introduced a new measure for evaluating the relationship between the gene and pathway, termed the percentile (p)-score, which enables users to predict functionally relevant pathways without being affected by the internal correlation in pathways. In addition, we evaluated our approaches using receiver operating characteristic curves, which concluded that the p-score could improve the performance of the ORA.We developed a new database, named Co-expressed Pathways DataBase for Tomato, which is available at http://cox-path-db.kazusa.or.jp/tomato . The database allows users to predict pathways that are relevant to a query gene, which would help to infer gene functions.

Dataset Information

A reference database for tumor-related genes co-expressed with interleukin-8 using genome-scale in silico analysis.

Publications

A reference database for tumor-related genes co-expressed with interleukin-8 using genome-scale in silico analysis.

Similar Datasets

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