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Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods.

Adler P, Kolde R, Kull M, Tkachenko A, Peterson H, Reimand J, Vilo J - Genome Biol. (2009)

Bottom Line: We present a web resource MEM (Multi-Experiment Matrix) for gene expression similarity searches across many datasets.MEM features large collections of microarray datasets and utilizes rank aggregation to merge information from different datasets into a single global ordering with simultaneous statistical significance estimation.Unique features of MEM include automatic detection, characterization and visualization of datasets that includes the strongest coexpression patterns.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Molecular and Cell Biology, Riia 23, 51010 Tartu, Estonia. adler@ut.ee

ABSTRACT
We present a web resource MEM (Multi-Experiment Matrix) for gene expression similarity searches across many datasets. MEM features large collections of microarray datasets and utilizes rank aggregation to merge information from different datasets into a single global ordering with simultaneous statistical significance estimation. Unique features of MEM include automatic detection, characterization and visualization of datasets that includes the strongest coexpression patterns. MEM is freely available at http://biit.cs.ut.ee/mem/.

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Functional descriptions of the modules found in the mouse coexpression network constructed with MEM. Annotations of the six largest modules are shown in (a). Two smaller modules are shown in the Figure, along with their functional annotations in (b) and (c).
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Figure 3: Functional descriptions of the modules found in the mouse coexpression network constructed with MEM. Annotations of the six largest modules are shown in (a). Two smaller modules are shown in the Figure, along with their functional annotations in (b) and (c).

Mentions: The size, density and functional descriptions of the six largest modules can be seen on Figure 3a. All have strong and clear functional annotations, that is, proteasome (KEGG, P < 10-11), mitochondria (GO, P < 10-146), cell cycle (GO, P < 10-50), biological adhesion (GO, P < 10-18), immune system process (GO, P < 10-21) and protein transport (GO, P < 10-5). Several smaller modules with interesting functional annotations are also detected, for instance one related to T-cell generation (Figure 3b, P < 10-12) and one related to regulation of heart contraction (Figure 3c, P < 10-7).


Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods.

Adler P, Kolde R, Kull M, Tkachenko A, Peterson H, Reimand J, Vilo J - Genome Biol. (2009)

Functional descriptions of the modules found in the mouse coexpression network constructed with MEM. Annotations of the six largest modules are shown in (a). Two smaller modules are shown in the Figure, along with their functional annotations in (b) and (c).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2812946&req=5

Figure 3: Functional descriptions of the modules found in the mouse coexpression network constructed with MEM. Annotations of the six largest modules are shown in (a). Two smaller modules are shown in the Figure, along with their functional annotations in (b) and (c).
Mentions: The size, density and functional descriptions of the six largest modules can be seen on Figure 3a. All have strong and clear functional annotations, that is, proteasome (KEGG, P < 10-11), mitochondria (GO, P < 10-146), cell cycle (GO, P < 10-50), biological adhesion (GO, P < 10-18), immune system process (GO, P < 10-21) and protein transport (GO, P < 10-5). Several smaller modules with interesting functional annotations are also detected, for instance one related to T-cell generation (Figure 3b, P < 10-12) and one related to regulation of heart contraction (Figure 3c, P < 10-7).

Bottom Line: We present a web resource MEM (Multi-Experiment Matrix) for gene expression similarity searches across many datasets.MEM features large collections of microarray datasets and utilizes rank aggregation to merge information from different datasets into a single global ordering with simultaneous statistical significance estimation.Unique features of MEM include automatic detection, characterization and visualization of datasets that includes the strongest coexpression patterns.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Molecular and Cell Biology, Riia 23, 51010 Tartu, Estonia. adler@ut.ee

ABSTRACT
We present a web resource MEM (Multi-Experiment Matrix) for gene expression similarity searches across many datasets. MEM features large collections of microarray datasets and utilizes rank aggregation to merge information from different datasets into a single global ordering with simultaneous statistical significance estimation. Unique features of MEM include automatic detection, characterization and visualization of datasets that includes the strongest coexpression patterns. MEM is freely available at http://biit.cs.ut.ee/mem/.

Show MeSH