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MCL coexpression mm9:266

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Phase1 CAGE Peaks

 Short description
Mm9::chr10:13685096..13685118,+p@chr10:13685096..13685118
+
Mm9::chr10:13685134..13685145,+p@chr10:13685134..13685145
+
Mm9::chr11:22758767..22758769,-p@chr11:22758767..22758769
-
Mm9::chr11:54336430..54336441,+p3@Rapgef6
Mm9::chr11:61466761..61466855,+p1@Grap
Mm9::chr11:61469831..61469835,+p@chr11:61469831..61469835
+
Mm9::chr11:61474548..61474552,+p@chr11:61474548..61474552
+
Mm9::chr11:61485697..61485720,+p@chr11:61485697..61485720
+
Mm9::chr11:80323299..80323300,+p@chr11:80323299..80323300
+
Mm9::chr13:3610228..3610244,-p7@BC016423
Mm9::chr13:51893902..51893927,-p@chr13:51893902..51893927
-
Mm9::chr14:122315029..122315085,-p1@Gpr18
Mm9::chr16:45224225..45224236,+p5@Btla
Mm9::chr16:45224284..45224305,+p1@Btla
Mm9::chr16:52144199..52144200,+p@chr16:52144199..52144200
+
Mm9::chr17:35331447..35331466,+p1@Ltb
Mm9::chr18:32557208..32557215,+p@chr18:32557208..32557215
+
Mm9::chr18:65576045..65576061,-p@chr18:65576045..65576061
-
Mm9::chr18:65590599..65590627,+p4@Malt1
Mm9::chr18:65590638..65590665,+p2@Malt1
Mm9::chr18:65590666..65590691,+p1@Malt1
Mm9::chr18:65590703..65590732,+p3@Malt1
Mm9::chr1:188335985..188335987,+p@chr1:188335985..188335987
+
Mm9::chr1:64579184..64579194,+p7@Creb1
Mm9::chr2:30915978..30915993,+p@chr2:30915978..30915993
+
Mm9::chr4:32325688..32325777,+p1@Bach2
Mm9::chr4:32325955..32325971,+p3@Bach2
Mm9::chr4:63064279..63064293,-p7@Akna
Mm9::chr4:63064303..63064308,-p9@Akna
Mm9::chr4:63064311..63064320,-p8@Akna
Mm9::chr6:48696222..48696233,+p3@Gimap5


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:0002768immune response-regulating cell surface receptor signaling pathway0.000174479123922689
GO:0002764immune response-regulating signal transduction0.000174479123922689
GO:0050856regulation of T cell receptor signaling pathway0.00101592759965883
GO:0050854regulation of antigen receptor-mediated signaling pathway0.00116331845102547
GO:0042110T cell activation0.00215079251463618
GO:0050852T cell receptor signaling pathway0.0021524670775335
GO:0050851antigen receptor-mediated signaling pathway0.00421913575959422
GO:0006955immune response0.00421913575959422
GO:0002429immune response-activating cell surface receptor signaling pathway0.00435844641325555
GO:0046649lymphocyte activation0.00435844641325555
GO:0002757immune response-activating signal transduction0.00468276709119705
GO:0045321leukocyte activation0.00468276709119705
GO:0001775cell activation0.00531614053961693
GO:0042098T cell proliferation0.00884527374803037
GO:0051239regulation of multicellular organismal process0.00902402382806831
GO:0001923B-1 B cell differentiation0.00902402382806831
GO:0002376immune system process0.00902402382806831
GO:0050863regulation of T cell activation0.00902402382806831
GO:0032943mononuclear cell proliferation0.0111916556393603
GO:0046651lymphocyte proliferation0.0111916556393603
GO:0002253activation of immune response0.0115352335980385
GO:0051249regulation of lymphocyte activation0.0119104786328979
GO:0042113B cell activation0.0119104786328979
GO:0050865regulation of cell activation0.0119104786328979
GO:0002335mature B cell differentiation0.0119104786328979
GO:0046642negative regulation of alpha-beta T cell proliferation0.0119104786328979
GO:0050778positive regulation of immune response0.0138950261258893
GO:0002684positive regulation of immune system process0.0139566917593426
GO:0046636negative regulation of alpha-beta T cell activation0.0160131525846775
GO:0050776regulation of immune response0.0166602235441313
GO:0002682regulation of immune system process0.0167007357964178
GO:0051240positive regulation of multicellular organismal process0.0173270067086378
GO:0050860negative regulation of T cell receptor signaling pathway0.0221012889037602
GO:0050858negative regulation of antigen receptor-mediated signaling pathway0.0221012889037602
GO:0046887positive regulation of hormone secretion0.0221012889037602
GO:0030889negative regulation of B cell proliferation0.0343515439631739
GO:0046640regulation of alpha-beta T cell proliferation0.0375907177745593
GO:0051047positive regulation of secretion0.0397860618734093
GO:0046983protein dimerization activity0.0397860618734093
GO:0050869negative regulation of B cell activation0.0414391459733394
GO:0046634regulation of alpha-beta T cell activation0.0414391459733394
GO:0046633alpha-beta T cell proliferation0.044117917155906
GO:0009620response to fungus0.0450123842535574
GO:0048534hemopoietic or lymphoid organ development0.0450123842535574
GO:0042130negative regulation of T cell proliferation0.0450123842535574
GO:0030693caspase activity0.0450123842535574
GO:0005070SH3/SH2 adaptor activity0.0450123842535574
GO:0051092activation of NF-kappaB transcription factor0.0450123842535574
GO:0007595lactation0.047230386028979
GO:0050789regulation of biological process0.0472530048063267
GO:0002520immune system development0.0472530048063267
GO:0005515protein binding0.0472530048063267
GO:0002237response to molecule of bacterial origin0.0478425321748572
GO:0048535lymph node development0.0478425321748572
GO:0050868negative regulation of T cell activation0.0478425321748572
GO:0021983pituitary gland development0.0478425321748572
GO:0032813tumor necrosis factor receptor superfamily binding0.0478425321748572
GO:0005164tumor necrosis factor receptor binding0.0478425321748572
GO:0050672negative regulation of lymphocyte proliferation0.0481484067149273
GO:0032945negative regulation of mononuclear cell proliferation0.0481484067149273
GO:0048518positive regulation of biological process0.0481484067149273
GO:0021536diencephalon development0.0481484067149273
GO:0051091positive regulation of transcription factor activity0.0481484067149273
GO:0046883regulation of hormone secretion0.0481484067149273
GO:0030888regulation of B cell proliferation0.0497644230015757
GO:0007154cell communication0.0498204843844854
GO:0040018positive regulation of multicellular organism growth0.0498204843844854
GO:0030879mammary gland development0.0498204843844854



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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