MCL coexpression mm9:266

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

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GO ID	GO name	FDR corrected p-value
GO:0002768	immune response-regulating cell surface receptor signaling pathway	0.000174479123922689
GO:0002764	immune response-regulating signal transduction	0.000174479123922689
GO:0050856	regulation of T cell receptor signaling pathway	0.00101592759965883
GO:0050854	regulation of antigen receptor-mediated signaling pathway	0.00116331845102547
GO:0042110	T cell activation	0.00215079251463618
GO:0050852	T cell receptor signaling pathway	0.0021524670775335
GO:0050851	antigen receptor-mediated signaling pathway	0.00421913575959422
GO:0006955	immune response	0.00421913575959422
GO:0002429	immune response-activating cell surface receptor signaling pathway	0.00435844641325555
GO:0046649	lymphocyte activation	0.00435844641325555
GO:0002757	immune response-activating signal transduction	0.00468276709119705
GO:0045321	leukocyte activation	0.00468276709119705
GO:0001775	cell activation	0.00531614053961693
GO:0042098	T cell proliferation	0.00884527374803037
GO:0051239	regulation of multicellular organismal process	0.00902402382806831
GO:0001923	B-1 B cell differentiation	0.00902402382806831
GO:0002376	immune system process	0.00902402382806831
GO:0050863	regulation of T cell activation	0.00902402382806831
GO:0032943	mononuclear cell proliferation	0.0111916556393603
GO:0046651	lymphocyte proliferation	0.0111916556393603
GO:0002253	activation of immune response	0.0115352335980385
GO:0051249	regulation of lymphocyte activation	0.0119104786328979
GO:0042113	B cell activation	0.0119104786328979
GO:0050865	regulation of cell activation	0.0119104786328979
GO:0002335	mature B cell differentiation	0.0119104786328979
GO:0046642	negative regulation of alpha-beta T cell proliferation	0.0119104786328979
GO:0050778	positive regulation of immune response	0.0138950261258893
GO:0002684	positive regulation of immune system process	0.0139566917593426
GO:0046636	negative regulation of alpha-beta T cell activation	0.0160131525846775
GO:0050776	regulation of immune response	0.0166602235441313
GO:0002682	regulation of immune system process	0.0167007357964178
GO:0051240	positive regulation of multicellular organismal process	0.0173270067086378
GO:0050860	negative regulation of T cell receptor signaling pathway	0.0221012889037602
GO:0050858	negative regulation of antigen receptor-mediated signaling pathway	0.0221012889037602
GO:0046887	positive regulation of hormone secretion	0.0221012889037602
GO:0030889	negative regulation of B cell proliferation	0.0343515439631739
GO:0046640	regulation of alpha-beta T cell proliferation	0.0375907177745593
GO:0051047	positive regulation of secretion	0.0397860618734093
GO:0046983	protein dimerization activity	0.0397860618734093
GO:0050869	negative regulation of B cell activation	0.0414391459733394
GO:0046634	regulation of alpha-beta T cell activation	0.0414391459733394
GO:0046633	alpha-beta T cell proliferation	0.044117917155906
GO:0009620	response to fungus	0.0450123842535574
GO:0048534	hemopoietic or lymphoid organ development	0.0450123842535574
GO:0042130	negative regulation of T cell proliferation	0.0450123842535574
GO:0030693	caspase activity	0.0450123842535574
GO:0005070	SH3/SH2 adaptor activity	0.0450123842535574
GO:0051092	activation of NF-kappaB transcription factor	0.0450123842535574
GO:0007595	lactation	0.047230386028979
GO:0050789	regulation of biological process	0.0472530048063267
GO:0002520	immune system development	0.0472530048063267
GO:0005515	protein binding	0.0472530048063267
GO:0002237	response to molecule of bacterial origin	0.0478425321748572
GO:0048535	lymph node development	0.0478425321748572
GO:0050868	negative regulation of T cell activation	0.0478425321748572
GO:0021983	pituitary gland development	0.0478425321748572
GO:0032813	tumor necrosis factor receptor superfamily binding	0.0478425321748572
GO:0005164	tumor necrosis factor receptor binding	0.0478425321748572
GO:0050672	negative regulation of lymphocyte proliferation	0.0481484067149273
GO:0032945	negative regulation of mononuclear cell proliferation	0.0481484067149273
GO:0048518	positive regulation of biological process	0.0481484067149273
GO:0021536	diencephalon development	0.0481484067149273
GO:0051091	positive regulation of transcription factor activity	0.0481484067149273
GO:0046883	regulation of hormone secretion	0.0481484067149273
GO:0030888	regulation of B cell proliferation	0.0497644230015757
GO:0007154	cell communication	0.0498204843844854
GO:0040018	positive regulation of multicellular organism growth	0.0498204843844854
GO:0030879	mammary gland development	0.0498204843844854

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

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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>

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Cell Type

Ontology term	p-value	n

Uber Anatomy

Ontology term	p-value	n

Disease

Ontology term	p-value	n

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

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Novel motifs

JASPAR motifs

Motifs	-log10(p-value)
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