کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9131857 | 1160954 | 2005 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Assessment and integration of publicly available SAGE, cDNA microarray, and oligonucleotide microarray expression data for global coexpression analyses
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کلمات کلیدی
mGCIEAGEOMCEMammalian Gene CollectionCoexpression - بیان عباراتGene expression - بیان ژنSerial analysis of gene expression - تجزیه و تحلیل سریال بیان ژنMicroarray analysis - تجزیه و تحلیل میکرواراSAGE - حکیمgene expression profiling - مشخصات ژن بیانcDNA microarray - میکروآرایه cDNAOligonucleotide microarray - میکروآرایه اولیگونوکلئوتیدGene ontology - هستیشناسی ژنیPearson correlation - همبستگی پیرسونGene Expression Omnibus - ژن بیان Omnibus
موضوعات مرتبط
علوم زیستی و بیوفناوری
بیوشیمی، ژنتیک و زیست شناسی مولکولی
ژنتیک
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Assessment and integration of publicly available SAGE, cDNA microarray, and oligonucleotide microarray expression data for global coexpression analyses Assessment and integration of publicly available SAGE, cDNA microarray, and oligonucleotide microarray expression data for global coexpression analyses](/preview/png/9131857.png)
چکیده انگلیسی
Large amounts of gene expression data from several different technologies are becoming available to the scientific community. A common practice is to use these data to calculate global gene coexpression for validation or integration of other “omic” data. To assess the utility of publicly available datasets for this purpose we have analyzed Homo sapiens data from 1202 cDNA microarray experiments, 242 SAGE libraries, and 667 Affymetrix oligonucleotide microarray experiments. The three datasets compared demonstrate significant but low levels of global concordance (rc < 0.11). Assessment against Gene Ontology (GO) revealed that all three platforms identify more coexpressed gene pairs with common biological processes than expected by chance. As the Pearson correlation for a gene pair increased it was more likely to be confirmed by GO. The Affymetrix dataset performed best individually with gene pairs of correlation 0.9-1.0 confirmed by GO in 74% of cases. However, in all cases, gene pairs confirmed by multiple platforms were more likely to be confirmed by GO. We show that combining results from different expression platforms increases reliability of coexpression. A comparison with other recently published coexpression studies found similar results in terms of performance against GO but with each method producing distinctly different gene pair lists.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Genomics - Volume 86, Issue 4, October 2005, Pages 476-488
Journal: Genomics - Volume 86, Issue 4, October 2005, Pages 476-488
نویسندگان
Obi L. Griffith, Erin D. Pleasance, Debra L. Fulton, Mehrdad Oveisi, Martin Ester, Asim S. Siddiqui, Steven J.M. Jones,