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MCL coexpression mm9:765: Difference between revisions

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{{MCL_coexpression_mm9
{{MCL_coexpression_mm9
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}}
}}

Revision as of 12:46, 11 October 2012


Phase1 CAGE Peaks

 Short description
Mm9::chr10:57909488..57909491,+p3@Ranbp2
Mm9::chr10:61957572..61957584,-p@chr10:61957572..61957584
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Mm9::chr10:61957587..61957611,-p@chr10:61957587..61957611
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Mm9::chr10:61957621..61957632,-p@chr10:61957621..61957632
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Mm9::chr10:61957717..61957729,-p@chr10:61957717..61957729
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Mm9::chr10:61960605..61960621,-p@chr10:61960605..61960621
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Mm9::chr10:61970485..61970512,-p1@Srgn
Mm9::chr17:57244824..57244844,+p1@Tnfsf9
Mm9::chr2:167877446..167877452,-p@chr2:167877446..167877452
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Enriched pathways on this co-expression cluster<b>Summary:</b><br>Canonical pathway gene sets were compiled from Reactome, Wikipathways and KEGG. For the major signaling pathways, the transcriptionally-regulated genes (downstream targets) were obtained from Netpath. Combined, the canonical pathways and downstream targets totaled 489 human gene sets. The corresponding M. musculus gene sets were inferred by homology using the HomoloGene database. Enrichment for each of the canonical 489 pathways and gene sets included in the co-expression cluster was assessed by the hypergeometric probability. The resulting P values were also then adjusted by the Benjamini-Hochberg method for multiple comparisons.<br><b>Analyst: </b>Emmanuel Dimont<br><br>link to source dataset<br>data


GO IDGO nameFDR corrected p-value
GO:0033371T cell secretory granule organization and biogenesis0.00143811976113516
GO:0033366protein localization in secretory granule0.00143811976113516
GO:0033377maintenance of protein localization in T cell secretory granule0.00143811976113516
GO:0033374protein localization in T cell secretory granule0.00143811976113516
GO:0033365protein localization in organelle0.00143811976113516
GO:0033370maintenance of protein localization in mast cell secretory granule0.00143811976113516
GO:0033382maintenance of granzyme B localization in T cell secretory granule0.00143811976113516
GO:0033375protease localization in T cell secretory granule0.00143811976113516
GO:0033373maintenance of protease localization in mast cell secretory granule0.00143811976113516
GO:0033367protein localization in mast cell secretory granule0.00143811976113516
GO:0033364mast cell secretory granule organization and biogenesis0.00143811976113516
GO:0042629mast cell granule0.00143811976113516
GO:0033368protease localization in mast cell secretory granule0.00143811976113516
GO:0033363secretory granule organization and biogenesis0.00143811976113516
GO:0033380granzyme B localization in T cell secretory granule0.00143811976113516
GO:0033379maintenance of protease localization in T cell secretory granule0.00143811976113516
GO:0050709negative regulation of protein secretion0.00383456581097931
GO:0050710negative regulation of cytokine secretion0.00383456581097931
GO:0050707regulation of cytokine secretion0.00605391414152312
GO:0050663cytokine secretion0.00690108397284551
GO:0045185maintenance of protein localization0.00940902219581238
GO:0051605protein maturation via proteolysis0.00940902219581238
GO:0051604protein maturation0.00999937901019018
GO:0016050vesicle organization and biogenesis0.0110381045952215
GO:0051048negative regulation of secretion0.0110381045952215
GO:0050708regulation of protein secretion0.0123811320450737
GO:0051235maintenance of localization0.0127734838112938
GO:0005164tumor necrosis factor receptor binding0.014268718486589
GO:0032813tumor necrosis factor receptor superfamily binding0.014268718486589
GO:0045184establishment of protein localization0.0176249390066471
GO:0008104protein localization0.0192594749502943
GO:0051649establishment of cellular localization0.0192594749502943
GO:0051641cellular localization0.0192594749502943
GO:0033036macromolecule localization0.0192594749502943
GO:0009306protein secretion0.0196914644386767
GO:0003755peptidyl-prolyl cis-trans isomerase activity0.0216923192976312
GO:0016859cis-trans isomerase activity0.0217256151948936
GO:0051028mRNA transport0.0271176221182818
GO:0050658RNA transport0.0271176221182818
GO:0051236establishment of RNA localization0.0271176221182818
GO:0050657nucleic acid transport0.0271176221182818
GO:0006403RNA localization0.0271176221182818
GO:0005643nuclear pore0.0271176221182818
GO:0051046regulation of secretion0.0271176221182818
GO:0065002intracellular protein transport across a membrane0.027333537098526
GO:0015931nucleobase, nucleoside, nucleotide and nucleic acid transport0.027333537098526
GO:0046930pore complex0.027333537098526
GO:0044453nuclear membrane part0.0291457452728465
GO:0031965nuclear membrane0.0294837957638816
GO:0001503ossification0.0421947015982399
GO:0031214biomineral formation0.0421947015982399
GO:0001816cytokine production0.0435725434786286
GO:0046849bone remodeling0.0444679453359891
GO:0005515protein binding0.0449187407769357
GO:0005635nuclear envelope0.0449187407769357
GO:0048771tissue remodeling0.0493916889321265



Relative expression of the co-expression cluster over median <br>Analyst:





Enriched sample ontology terms on this co-expression cluster<b>Summary:</b>To summarize promoter activities (expression profile of a TSS region) across ~1000 samples, we performed enrichment analysis based on FANTOM5 Sample Ontology (FF ontology). The question here is “in which type of samples the promoter is more active”. To answer this question, we compared expressions (TPMs) in the samples associated with a sample ontology term and the rest of the samples by using the Mann-Whitney rank sum test. To summarize ontologies enriched in this co-expression cluster, we ran the same analysis on an averaged expression profile of all promoters that make up. <b>Analyst:</b> Hideya Kawaji <br><br>links to source dataset<br><br>cell_data<br>uberon_data<br>disease_data<br>


Cell Type
Ontology termp-valuen

Uber Anatomy
Ontology termp-valuen

Disease
Ontology termp-valuen


TFBS overrepresentation<b>Summary:</b>The values shown are the p-values for overrepresentation of the motif in this coexpression cluster. So a small p-value means a strong overrepresentation. <b>Analyst:</b> Michiel de Hoon <br><br>link to source data <br> Novel motifs <br>data <br><br> Jaspar motifs <br>data


Novel motifs




JASPAR motifs


Motifs-log10(p-value)

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