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{{Coexpression_clusters
{
|coexpression_dpi_cluster_scores_median=0,0,0

Latest revision as of 11:29, 17 September 2013


Full id: C730_migratory_cord_Mast_B_b_CD14_CD19



Phase1 CAGE Peaks

Hg19::chr11:102188181..102188222,+p1@BIRC3
Hg19::chr12:97286249..97286254,+p@chr12:97286249..97286254
+
Hg19::chr13:44272246..44272260,-p@chr13:44272246..44272260
-
Hg19::chr2:231808435..231808449,+p@chr2:231808435..231808449
+
Hg19::chr2:231808494..231808516,+p@chr2:231808494..231808516
+
Hg19::chr2:231808538..231808549,+p@chr2:231808538..231808549
+
Hg19::chr2:231808553..231808564,+p@chr2:231808553..231808564
+
Hg19::chr3:119278446..119278477,-p1@CD80
Hg19::chr3:119278493..119278513,-p3@CD80
Hg19::chr3:71114563..71114584,-p49@FOXP1
Hg19::chr6:138192133..138192144,+p19@TNFAIP3


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


p.valueFDRnGenesnPathwayName
2.51303723965872e-050.0159075257270397259NOD-like receptor signaling pathway (KEGG):04621
0.0001423689371822350.0301654177358552140Regulation of toll-like receptor signaling pathway (Wikipathways):WP1449
0.0002566225776512870.03248841833065292188TNF-alpha/NF-kB Signaling Pathway (Wikipathways):WP231
0.0001906187534651180.0301654177358552162TNF alpha/NF-kB down reg. targets (Netpath):NetPath_9
0.0004387476209653280.04628787401184212246B Cell Receptor up reg. targets (Netpath):NetPath_12
0.0001745097179976610.0301654177358552155IL-1 up reg. targets (Netpath):NetPath_13



Enriched Gene Ontology terms on this co-expression cluster<b>Summary:</b> Results for GOStat analysis on co-expressed clusters. Each cluster with promoters mapping to at least two different genes was analysed with GOStat (PMID: 14962934) with default parameter. <br><b>Analyst:</b> Erik Arner<br><br>link to source dataset<br>data


GO IDGO nameFDR corrected p-value
GO:0006916anti-apoptosis0.00846701689959302
GO:0045627positive regulation of T-helper 1 cell differentiation0.00846701689959302
GO:0043066negative regulation of apoptosis0.00846701689959302
GO:0043069negative regulation of programmed cell death0.00846701689959302
GO:0045425positive regulation of granulocyte macrophage colony-stimulating factor biosynthetic process0.00846701689959302
GO:0045625regulation of T-helper 1 cell differentiation0.00846701689959302
GO:0045624positive regulation of T-helper cell differentiation0.00846701689959302
GO:0045423regulation of granulocyte macrophage colony-stimulating factor biosynthetic process0.00846701689959302
GO:0045063T-helper 1 cell differentiation0.00846701689959302
GO:0048869cellular developmental process0.00846701689959302
GO:0030154cell differentiation0.00846701689959302
GO:0032604granulocyte macrophage colony-stimulating factor production0.00846701689959302
GO:0042253granulocyte macrophage colony-stimulating factor biosynthetic process0.00846701689959302
GO:0043124negative regulation of I-kappaB kinase/NF-kappaB cascade0.0088037535985753
GO:0050794regulation of cellular process0.0088037535985753
GO:0045622regulation of T-helper cell differentiation0.0088037535985753
GO:0050789regulation of biological process0.0088037535985753
GO:0002294CD4-positive, alpha-beta T cell differentiation during immune response0.0088037535985753
GO:0002292T cell differentiation during immune response0.0088037535985753
GO:0042093T-helper cell differentiation0.0088037535985753
GO:0002366leukocyte activation during immune response0.0088037535985753
GO:0002285lymphocyte activation during immune response0.0088037535985753
GO:0002293alpha-beta T cell differentiation during immune response0.0088037535985753
GO:0002286T cell activation during immune response0.0088037535985753
GO:0002263cell activation during immune response0.0088037535985753
GO:0043367CD4-positive, alpha beta T cell differentiation0.00896639012394077
GO:0045086positive regulation of interleukin-2 biosynthetic process0.00896639012394077
GO:0042088T-helper 1 type immune response0.00943176012279184
GO:0065007biological regulation0.00993040632193333
GO:0042981regulation of apoptosis0.0100587672340465
GO:0043067regulation of programmed cell death0.0100587672340465
GO:0045076regulation of interleukin-2 biosynthetic process0.0100587672340465
GO:0015026coreceptor activity0.0100587672340465
GO:0042094interleukin-2 biosynthetic process0.0100587672340465
GO:0046632alpha-beta T cell differentiation0.0100587672340465
GO:0050731positive regulation of peptidyl-tyrosine phosphorylation0.0103901080152437
GO:0046631alpha-beta T cell activation0.0112976251774761
GO:0032623interleukin-2 production0.0121571738180355
GO:0042327positive regulation of phosphorylation0.0129724438466746
GO:0045937positive regulation of phosphate metabolic process0.0136838464624472
GO:0001934positive regulation of protein amino acid phosphorylation0.0136838464624472
GO:0033240positive regulation of amine metabolic process0.0136838464624472
GO:0045764positive regulation of amino acid metabolic process0.0136838464624472
GO:0009966regulation of signal transduction0.0136838464624472
GO:0050730regulation of peptidyl-tyrosine phosphorylation0.0136838464624472
GO:0032502developmental process0.0143908452919003
GO:0006915apoptosis0.0145299318049594
GO:0012501programmed cell death0.0145299318049594
GO:0008219cell death0.0154497464175671
GO:0016265death0.0154497464175671
GO:0042108positive regulation of cytokine biosynthetic process0.0173298119070996
GO:0030217T cell differentiation0.0173298119070996
GO:0018108peptidyl-tyrosine phosphorylation0.017416768372748
GO:0018212peptidyl-tyrosine modification0.0177337429088587
GO:0001932regulation of protein amino acid phosphorylation0.0177337429088587
GO:0033238regulation of amine metabolic process0.0177337429088587
GO:0006521regulation of amino acid metabolic process0.0177337429088587
GO:0045727positive regulation of translation0.0200738668320086
GO:0048523negative regulation of cellular process0.0203475436230452
GO:0008270zinc ion binding0.0207769642665428
GO:0048519negative regulation of biological process0.0209150828709926
GO:0042035regulation of cytokine biosynthetic process0.0209150828709926
GO:0031328positive regulation of cellular biosynthetic process0.0209150828709926
GO:0042325regulation of phosphorylation0.0216146228805791
GO:0030098lymphocyte differentiation0.0216146228805791
GO:0048468cell development0.0216146228805791
GO:0042089cytokine biosynthetic process0.021638507126761
GO:0042107cytokine metabolic process0.021638507126761
GO:0051174regulation of phosphorus metabolic process0.021638507126761
GO:0019220regulation of phosphate metabolic process0.021638507126761
GO:0009891positive regulation of biosynthetic process0.0216419680822234
GO:0002250adaptive immune response0.0228471846603561
GO:0002460adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains0.0228471846603561
GO:0051247positive regulation of protein metabolic process0.0251974450950482
GO:0002521leukocyte differentiation0.0263181054783823
GO:0046914transition metal ion binding0.0263418696564084
GO:0042110T cell activation0.0279032791360802
GO:0009968negative regulation of signal transduction0.0290930201859787
GO:0007165signal transduction0.0290930201859787
GO:0043122regulation of I-kappaB kinase/NF-kappaB cascade0.0295843340928558
GO:0001816cytokine production0.030565078760423
GO:0018193peptidyl-amino acid modification0.0323184193172839
GO:0007154cell communication0.0346449739125504
GO:0007249I-kappaB kinase/NF-kappaB cascade0.0362133505252718
GO:0045595regulation of cell differentiation0.0370664343864876
GO:0009967positive regulation of signal transduction0.038909666557327
GO:0046649lymphocyte activation0.0389617623384476
GO:0007242intracellular signaling cascade0.039422872973318
GO:0030097hemopoiesis0.0395500346220457
GO:0004842ubiquitin-protein ligase activity0.0398340772845374
GO:0008639small protein conjugating enzyme activity0.0398732590749438
GO:0005634nucleus0.0399241594957774
GO:0048534hemopoietic or lymphoid organ development0.0406484365205676
GO:0045321leukocyte activation0.041830301086174
GO:0002520immune system development0.0418461718831951
GO:0006417regulation of translation0.0418616318815704
GO:0031326regulation of cellular biosynthetic process0.0447778243296604
GO:0043687post-translational protein modification0.0452550749111929
GO:0043169cation binding0.0452550749111929
GO:0001775cell activation0.045596969066149
GO:0009889regulation of biosynthetic process0.046856999686847



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
leukocyte5.03e-28136
hematopoietic lineage restricted progenitor cell2.54e-26120
nongranular leukocyte1.04e-25115
hematopoietic cell1.99e-24177
hematopoietic oligopotent progenitor cell2.00e-22161
hematopoietic multipotent progenitor cell2.00e-22161
hematopoietic stem cell3.73e-21168
angioblastic mesenchymal cell3.73e-21168
lymphocyte of B lineage3.63e-1824
pro-B cell3.63e-1824
conventional dendritic cell3.57e-168
lymphoid lineage restricted progenitor cell5.27e-1652
lymphocyte1.24e-1553
common lymphoid progenitor1.24e-1553
nucleate cell6.30e-1555
Langerhans cell2.50e-145
classical monocyte2.70e-1342
CD14-positive, CD16-negative classical monocyte2.70e-1342
dendritic cell4.14e-1310
macrophage dendritic cell progenitor9.64e-1361
monopoietic cell1.86e-1159
monocyte1.86e-1159
monoblast1.86e-1159
promonocyte1.86e-1159
granulocyte monocyte progenitor cell2.69e-1167
defensive cell2.81e-1148
phagocyte2.81e-1148
myeloid lineage restricted progenitor cell6.52e-1066
myeloid cell7.21e-09108
common myeloid progenitor7.21e-09108
myeloid leukocyte7.89e-0972
circulating cell4.07e-076
Uber Anatomy
Ontology termp-valuen
hemopoietic organ1.65e-197
immune organ1.65e-197
hematopoietic system3.62e-1998
blood island3.62e-1998
hemolymphoid system1.79e-18108
immune system1.21e-1693
spleen2.62e-123
gastrointestinal system mesentery2.62e-123
stomach region2.62e-123
mesentery2.62e-123
gastrointestinal system serosa2.62e-123
mesentery of stomach2.62e-123
gut mesentery2.62e-123
dorsal mesentery2.62e-123
dorsal mesogastrium2.62e-123
peritoneal cavity2.62e-123
spleen primordium2.62e-123
bone marrow1.48e-0976
thymus2.46e-094
hemolymphoid system gland2.46e-094
thymic region2.46e-094
pharyngeal gland2.46e-094
thymus primordium2.46e-094
bone element1.30e-0882
skeletal element1.49e-0790
Disease
Ontology termp-valuen
lymphoma1.45e-0910


Overrepresented TFBS (DNA) motifs on this co-expression cluster<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)
MA0003.10.000970254
MA0004.10.349539
MA0006.10.210781
MA0007.10.332734
MA0009.10.79061
MA0014.10.00227771
MA0017.10.24363
MA0019.10.486183
MA0024.10.688373
MA0025.10.921763
MA0027.12.39404
MA0028.10.224112
MA0029.10.707146
MA0030.10.696006
MA0031.10.633489
MA0038.11.12886
MA0040.10.712837
MA0041.10.366339
MA0042.10.895841
MA0043.10.790919
MA0046.10.779945
MA0048.10.41425
MA0050.10.338274
MA0051.10.439895
MA0052.10.716602
MA0055.10.279754
MA0056.10
MA0057.11.08492
MA0058.10.265212
MA0059.10.2641
MA0060.10.119532
MA0061.11.12119
MA0063.10
MA0066.10.444231
MA0067.11.1037
MA0068.15.43539
MA0069.10.776171
MA0070.10.765217
MA0071.10.40788
MA0072.10.760818
MA0073.10.304769
MA0074.10.439193
MA0076.10.278993
MA0077.10.753278
MA0078.10.533387
MA0081.10.730303
MA0083.10.79797
MA0084.11.28962
MA0087.10.758426
MA0088.11.96756
MA0089.10
MA0090.10.291627
MA0091.10.351901
MA0092.11.53836
MA0093.10.213288
MA0095.10
MA0098.10
MA0100.10.456802
MA0101.11.81378
MA0103.10.203171
MA0105.11.43099
MA0106.10.482519
MA0107.12.12117
MA0108.20.630531
MA0109.10
MA0111.10.303543
MA0113.10.498009
MA0114.10.153042
MA0115.11.02805
MA0116.10.159642
MA0117.10.827487
MA0119.11.99621
MA0122.10.852927
MA0124.10.98702
MA0125.10.904129
MA0130.10
MA0131.10.550695
MA0132.10
MA0133.10
MA0135.10.820382
MA0136.10.450422
MA0139.10.307853
MA0140.10.405425
MA0141.10.2626
MA0142.10.602852
MA0143.10.498176
MA0144.10.438224
MA0145.10.02761
MA0146.10.315774
MA0147.10.162359
MA0148.10.372124
MA0149.10.396509
MA0062.20.320507
MA0035.20.404774
MA0039.20.267159
MA0138.23.34637
MA0002.20.358551
MA0137.20.649788
MA0104.20.118985
MA0047.20.47109
MA0112.20.0251803
MA0065.20.0286783
MA0150.10.781086
MA0151.10
MA0152.10.411494
MA0153.10.887528
MA0154.10.353037
MA0155.10.099499
MA0156.10.231442
MA0157.10.576556
MA0158.10
MA0159.10.162854
MA0160.10.386031
MA0161.10
MA0162.10.00470038
MA0163.10.232847
MA0164.10.509774
MA0080.20.21336
MA0018.20.483823
MA0099.20.411824
MA0079.20.0905633
MA0102.21.32663
MA0258.10.135061
MA0259.10.168926
MA0442.10



ENCODE TF ChIP-seq peak enrichment analysis<b>Summary:</b> For each TF and each co-expression cluster, the number of promoters with ENCODE TF ChIP signal was compared with the rest of promoters from the robust set using Fisher's exact test. Clusters with significant ChIP enrichment (q <= 0.05) after Benjamini-Hochberg correction were retained. <br><b>Analyst:</b> Erik Arner<br><br>link to source dataset<br><br>data


(#promoters = Number of promoters in this coexpression cluster that have ChIP signal of the TF)

TF#promotersEnrichmentp-valueq-value
CHD2#110654.701828560962210.002363882154558910.0133963583667035
MEF2A#4205711.92751057886443.34835558215856e-071.66444030768709e-05
MYC#460973.323270281933260.001501335996249240.00959068017079174
NFKB1#4790104.989148567448943.69910541950576e-071.8223154288102e-05
POU2F2#545275.794806218563424.24433119609668e-050.000759550558240475
SPI1#668864.475085550103310.0008746501340011530.00652482752463903
TBP#690882.695833226979190.002040852110349220.0118505812049795
YY1#752873.125290477179730.002193839507732880.0126440265078149
ZBTB33#10009411.51444546544770.0002743430759209510.00292517779541686



Relative expression of the co-expression cluster<b>Summary:</b>Co-expression clusters are compared against FANTOM5 samples to obtain relative expression. <br><b>Analyst:</b>NA<br><br>link to data source<br> data


This analysis result is provided for C0 - C305 clusters.