Meta Analysis Home

About Meta Analysis

The Meta Analysis Tool shows expression comparisons derived from studies found in the genomics section of the Beta Cell Biology Consortium. The results are displayed as a heat map with genes as rows and study comparisons as columns.

The Adobe Flash plugin is required to use this tool.

Operating Instructions:

Results page:

The results page displays a heatmap with the specified genes as rows and study comparisons as columns. Each comparison is obtained from one of three types of analyses:

(A) pairwise differential expression,
(B) one-condition time series,
(C) two-condition time series.

Heatmap Legend
For analyses of type A:

A red cell (labeled with 1) indicates that the gene is significantly up-regulated in that pairwise comparison.
A green cell (labeled with -1) indicates that the gene is significantly down-regulated in that pairwise comparison.

For analyses of types B and C:

A blue cell (labeled with Y) indicates that the gene is significant in that analysis (differentially expressed across time for type B or differentially expressed between the two conditions across time for type C).

For all analyses:

A black cell indicates that there is no evidence that that gene is significant with at least 80% confidence in that analysis.
A grey cell (labeled with NA) indicates that either the analysis could not be carried out (e.g. the gene was not monitored in that study or the study did not have enough replicates to carry out a statistical analysis) or that there was a conflict for that gene.

Filtering Level
You can select which results are displayed by choosing one of the options in the drop-down menu:

"Show columns with changed/significant data" displays study comparisons where gene expression is significantly different in at least one gene. This is the default view.
"Show columns with any data" displays study comparisons where gene expression is significantly different or study comparisons where gene expression is not altered in at least one gene.
"Show all columns" displays all study comparisons including those where gene expression is labeled as NA for all genes.

Additional Options
Clicking on a gene takes you to the gene page for that gene and clicking on a column label takes you to the study in the genomics section of the Beta Cell Biology Consortium.

If a gene identifier matches multiple genes, a box will be displayed on the results page saying "There were ambiguous terms in your query. Click here to resolve them." You can click the link to correct the identifier. To pick the correct identifier(s), click on the box next to the appropriate identifier(s) and click on Submit Corrections. A new results page with the correct identifier(s) will be shown.

You can add a gene to the heatmap by typing a gene identifier in the "Add a new gene box" and clicking Go.

You can save the displayed genes by clicking the "save list to My T1DBase" link at the top of the page. You can use the genes in another T1DBase program by clicking the "send list to tool" link at the top of the page. Clicking on one of the tools will cause a new page to be loaded with the gene list already included in the "Select a T1DBase List".

Scientific details:

The Meta Analysis Tool shows expression comparisons derived from studies found in the genomics section of the Beta Cell Biology Consortium. A list of these studies is shown in the table below. The results are shown as a heat map with genes as rows and study comparisons as columns. Each comparison is obtained from one of three types of analyses: pairwise differential expression, one-condition time series, and two-condition time series.

Pairwise differential expression analyses are performed on studies examining (at least) two conditions with at least three (biological) replicates per condition. Lists of genes which are likely to be differentially expressed between pairs of conditions are generated using PaGE, with a False Discovery Rate (FDR) of 20% (confidence of 80%).

One-condition time series analyses are performed on studies examining one condition across time. Lists of differentially expressed genes across time points are generated with EDGE, selecting genes with q-values <=20% (FDR of 20%, confidence of 80%).

Two-condition time series analyses are performed on studies examining two conditions across time. Lists of differentially expressed genes between the two conditions across time points are again generated with EDGE, with an FDR of 20%.

All analyses are carried out at the reporter level. A gene might be represented by multiple reporters on an array. For a gene to be called significant in a comparison, it must have at least one reporter with confidence greater than 80% in the corresponding analysis, and there must be no conflicts (i.e., for pairwise expression comparisons, no two reporters for that gene of which one is significantly up and the other significantly down regulated).

A List of Studies used in the Meta Analysis Tool.

Study Name	Species in Study	Reference or Contact for Study
Human pancreatic cultures	Human	Susan Bonner-Weir (Harvard University)
Nestin positive cells vs human islets	Human	Joel F. Habener (Massachusetts General Hospital/HHMI)
Panc-1 Cell Differentiation	Human	Marvin Gershengorn (NIDDK Intramural)
Suspension Differentiation of fibroblast-like pancreatic progenitors	Human	Lucas Chase (Stem Cell Institute)
Human pancreatic islets from normal and Type 2 diabetic subjects	Human	[1]
A Gene Expression Network Model of Type 2 Diabetes Links Cell Cycle	Mouse	[2]
Cyclophosphamide-induced beta Cell Destruction in NOD Mice	Mouse	[3]
Overexpression of Neurogenin3 in Mpac mouse ductal cells	Mouse	[4]
Pancreatic Growth after Partial Pancreatectomy and Exendin-4 Treatment	Mouse	[5]
foxA1 and beta cell function	Mouse	[6]
Beta cell specific ablation of Foxa2 (HNF-3b) in mice	Mouse	[7]
Foxa2 controls vesicle docking and insulin secretion in mature beta-cells	Mouse	[8]
HNF4alpha in beta cell function	Mouse	[6]
Gene Expression Profiling of a Mouse Model of Pancreatic Islet Dysmorphogenesis	Mouse	[9]
Expression profiles of novel pancreatic cell lines	Mouse	Mark Magnuson (Vanderbilt University)
Neurogenin3 deficiency and Embryonic Pancreatic Gene Expression	Mouse	[10]
Profile of Neurogenin3 Expression Throughout Embryonic Development of the Endocrine Pancreas in Mice	Mouse	[11]
Ngn3-mediated differentiation of mouse embryonic stem cells into endocrine pancreas progenitors	Mouse	[12]
Affymetrix MOE430v2 vs Mouse PancChip 5.0 comparison	Mouse	Klaus Kaestner (University of Pennsylvania)
PANDER Induced Cell-Death Networks in Pancreatic Islets	Mouse	[13]
Sox4 null mice e12.5 pancreas	Mouse	[14]
Survivin transgenic mice pancreatic islet profile	Mouse	[15]
Beta Cell Growth in Tcf-1 Deficient Mice	Mouse	[16]
Lipotoxicity Study of Rat INS1 cell lines	Rat	[6]
Cytokine induced dysfunction and apoptosis in insulin producing INS1 Cells	Rat	[17]
GSIS Study of Rat INS1 cell lines	Rat	[6]
Cytotoxicity Study of Rat INS1 cell lines	Rat	Christopher Newgard (Duke University)
Stimulation of Human and Rat Islet beta-Cell Proliferation with Retention of Function by Nkx6.1	Rat	[18]

[1] Gunton JE, Kulkarni RN, Yim S, Okada T, Hawthorne WJ, Tseng YH, Roberson RS, Ricordi C, O'Connell PJ, Gonzalez FJ, Kahn CR (2005) Loss of ARNT/HIF1beta mediates altered gene expression and pancreatic-islet dysfunction in human type 2 diabetes. Cell. 122(3):337-49. PMID: 16096055

[2] Keller MP, Choi Y, Wang P, Davis DB, Rabaglia ME, Oler AT, Stapleton DS, Argmann C, Schueler KL, Edwards S, Steinberg HA, Chaibub Neto E, Kleinhanz R, Turner S, Hellerstein MK, Schadt EE, Yandell BS, Kendziorski C, Attie AD (2008) A gene expression network model of type 2 diabetes links cell cycle regulation in islets with diabetes susceptibility. Genome Res. 18(5):706-16. PMID: 18347327

[3] Matos M, Park R, Mathis D, Benoist C (2004) Progression to islet destruction in a cyclophosphamide-induced transgenic model: a microarray overview. Diabetes. 53(9):2310-21. PMID: 15331540

[4] Gasa R, Mrejen C, Leachman N, Otten M, Barnes M, Wang J, Chakrabarti S, Mirmira R, German M (2004) Proendocrine genes coordinate the pancreatic islet differentiation program in vitro. Proc Natl Acad Sci U S A. 101(36):13245-50. PMID: 15340143

[5] De León DD, Farzad C, Crutchlow MF, Brestelli J, Tobias J, Kaestner KH, Stoffers DA (2006) Identification of transcriptional targets during pancreatic growth after partial pancreatectomy and exendin-4 treatment. Physiol Genomics. 24(2):133-43. PMID: 16410542

[6] Hardy OT, Hohmeier HE, Becker TC, Manduchi E, Doliba NM, Gupta RK, White P, Stoeckert CJ Jr, Matschinsky FM, Newgard CB, Kaestner KH (2007) Functional genomics of the beta-cell: short-chain 3-hydroxyacyl-coenzyme A dehydrogenase regulates insulin secretion independent of K+ currents. Mol Endocrinol. 21(3):765-73. PMID: 17185391

[7] Lantz KA, Vatamaniuk MZ, Brestelli JE, Friedman JR, Matschinsky FM, Kaestner KH (2004) Foxa2 regulates multiple pathways of insulin secretion. J Clin Invest. 114(4):512-20. PMID: 15314688

[8] Gao N, White P, Doliba N, Golson ML, Matschinsky FM, Kaestner KH (2007) Foxa2 controls vesicle docking and insulin secretion in mature Beta cells. Cell Metab. 6(4):267-79. PMID: 17908556

[9] Wilding Crawford L, Tweedie Ables E, Oh YA, Boone B, Levy S, Gannon M (2008) Gene expression profiling of a mouse model of pancreatic islet dysmorphogenesis. PLoS ONE. 3(2):e1611. PMID: 18297134

[10] Petri A, Ahnfelt-Rønne J, Frederiksen KS, Edwards DG, Madsen D, Serup P, Fleckner J, Heller RS (2006) The effect of neurogenin3 deficiency on pancreatic gene expression in embryonic mice. J Mol Endocrinol. 37(2):301-16. PMID: 17032746

[11] White P, May CL, Lamounier RN, Brestelli JE, Kaestner KH (2008) Defining pancreatic endocrine precursors and their descendants. Diabetes. 57(3):654-68. PMID: 18071024

[12] Serafimidis I, Rakatzi I, Episkopou V, Gouti M, Gavalas A (2008) Novel effectors of directed and Ngn3-mediated differentiation of mouse embryonic stem cells into endocrine pancreas progenitors. Stem Cells. 26(1):3-16. PMID: 17932425

[13] Burkhardt BR, Greene SR, White P, Wong RK, Brestelli JE, Yang J, Robert CE, Brusko TM, Wasserfall CH, Wu J, Atkinson MA, Gao Z, Kaestner KH, Wolf BA (2006) PANDER-induced cell-death genetic networks in islets reveal central role for caspase-3 and cyclin-dependent kinase inhibitor 1A (p21). Gene. 369:134-41. PMID: 16412588

[14] Wilson ME, Yang KY, Kalousova A, Lau J, Kosaka Y, Lynn FC, Wang J, Mrejen C, Episkopou V, Clevers HC, German MS (2005) The HMG box transcription factor Sox4 contributes to the development of the endocrine pancreas. Diabetes. 54(12):3402-9. PMID: 16306355

[15] Dohi T, Salz W, Costa M, Ariyan C, Basadonna GP, Altieri DC (2006) Inhibition of apoptosis by survivin improves transplantation of pancreatic islets for treatment of diabetes in mice. EMBO Rep. 7(4):438-43. PMID: 16470228

[16] Akpinar P, Kuwajima S, Krützfeldt J, Stoffel M. (2005) Tmem27: a cleaved and shed plasma membrane protein that stimulates pancreatic beta cell proliferation. Cell Metab. 2(6):385-97. PMID: 16330324

[17] Kutlu B, Cardozo AK, Darville MI, Kruhøffer M, Magnusson N, Ørntoft T, Eizirik DL (2003) Discovery of gene networks regulating cytokine-induced dysfunction and apoptosis in insulin-producing INS-1 cells. Diabetes. 52(11):2701-19. PMID: 14578289

[18] Schisler JC, Fueger PT, Babu DA, Hohmeier HE, Tessem JS, Lu D, Becker TC, Naziruddin B, Levy M, Mirmira RG, Newgard CB (2008) Stimulation of human and rat islet beta-cell proliferation with retention of function by the homeodomain transcription factor Nkx6.1. Mol Cell Biol. 28(10):3465-76. PMID: 18347054

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Examples:

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Enter gene identifiers (one per line).
Either type them into the box below or upload a file.

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