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WP8: Computational analysis of beta-cell modular organization. EuroDia Meeting Lund, 23-25 February 2009. Sven Bergmann Department of Medical Genetics, UNIL & Swiss Institute of Bioinformatics. http://serverdgm.unil.ch/bergmann. Iterative Signature Algorithm.

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Sven Bergmann Department of Medical Genetics, UNIL & Swiss Institute of Bioinformatics

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Sven bergmann department of medical genetics unil swiss institute of bioinformatics

WP8:Computational analysis of beta-cell modular organization

EuroDia Meeting

Lund, 23-25 February 2009

Sven Bergmann

Department of Medical Genetics, UNIL &

Swiss Institute of Bioinformatics

http://serverdgm.unil.ch/bergmann


Iterative signature algorithm

Iterative Signature Algorithm

  • Unsupervised large-scale data analysis tool

  • Modularizes the expression matrix

  • Reduction of complexity

  • Allows for easy data integration

  • Interactive webtool


Modular analysis

Modular Analysis

  • A block of the reordered expression matrix

  • Genes and samples have scores

  • Captures differential co-expression

Transcription Module


Non modular analysis

Non-modular Analysis


Modular analysis1

Modular Analysis


Sven bergmann department of medical genetics unil swiss institute of bioinformatics

Gábor Csárdi and Sven Bergmann

Computational Biology Group,

Department of Medical Genetics,

University of Lausanne,

Switzerland

Modular Analysis of Multi-tissue Gene Expression Data


The data set

The Data Set

  • Coming from WP2, Frans Schuit's group.

  • C57bl6 mice, plus 7 S/A islet samples

  • 23 different tissues: adrenal gland, bone marrow, brain, diaphragma, ES cells, eye, fat, fetal, gastrocnemius muscle, heart, islet, kidney, liver, lung, ovary, parotis gland, pituitary gland, placenta, seminal vesicles, small intestine, spleen, testis, thymus.

  • 3-5 samples/tissue, 89 altogether

  • 19 islet samples, 8 on high fat diet

  • After filtering based on variance: 14,540 of 45,101 probesets left on the mouse4302 array


Batch and tissue effects

Batch and Tissue Effects

Pituary gland

Islets


Sven bergmann department of medical genetics unil swiss institute of bioinformatics

Spearman Rank correlation between 75 Affy mouse 430 2.0 arrays

TISSUE (n arrays)‏

High Fat Diet (5)‏

1

Islets

2

Standard Diet (4)‏

3

Pancreatic acini (3)‏

4

Adrenal (3)‏

5

Brain (3)‏

6

ES cells (3)‏

7

Adipose tissue (3)‏

8

Eye (3)‏

9

Heart (3)‏

10

Small intestine (3)‏

11

Hypothalamus (3)‏

12

Liver (3)‏

13

Lung(3)‏

14

Kidney (3)‏

15

Parotis gland (3)‏

16

Spleen (3)‏

17

Seminal vesicles (3)‏

18

Testis (3)‏

19

Thymus (3)‏

20

Diafragm (3)‏

21

Skeletal muscle (4)‏

Pituitary gland (5)‏

22

Bone marrow (4)‏

23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23


Very preliminary modular analysis results

Very preliminaryModular Analysis Results

  • 977 transcription modules were identified

  • High enrichment by tissues, GO categories, KEGG pathways and transcription factors

  • Condition plots

  • Show tissue specific modules

http://www2.unil.ch/cbg/Eurodia/isa3-html/maintable.html


Pancreas specific modules islets contaminating exocrine cells

Pancreas-Specific Modules(Islets + contaminating exocrine cells)‏

  • Example: #49, 35 probes, 27 Entrez genes, 43 conditions, 19 islet samples with positive scores

  • Many pancreas related genes


Pancreas specific modules

Pancreas-Specific Modules

  • Genes: Gcg, Iapp, Abcc8, Scn9a, Prss2, Pnlip, Ela3, Rab37, Cuzd1, Pnliprp2, Clps, Rnase1, Asb6, Ctrb1, BC039632, B830017H08Rik, A930021C24Rik, 2210010C04Rik, 1810049H19Rik


Pancreas specific modules1

Pancreas-specific Modules

  • Module #49

  • Differentiates between islets and other tissues


Islet specific go enrichment

Islet specific GO enrichment

P-value#Category

5.03e-749digestion

1.25e-1210extracellular region

3.18e-520mitochondrion

1.44e-425proton-transporting ATP synthase

complex, catalytic core F(1)‏

1.04e-664serine-type endopeptidase activity1.49e-4151endopeptidase activity

3.33e-416structural constituent of ribosome


Islet specific kegg enrichment

Islet specific KEGG enrichment

P-value#Category

4.37e-616Ribosome

3.26e-4155Oxidative phosphorylation


Islet specific mirnas

Islet specific miRNAs

P-value#Category

6.65e-3892miR-30 family


Islets only analysis

Islets-only Analysis


High fat diet islets

High Fat Diet Islets

  • Running ISA on the 19 islet samples only

  • Only 8,288 probesets after filtering

  • Module #41 differentiates between HF/LF diets best:

http://www2.unil.ch/cbg/Eurodia/isa5-html/maintable.html


High fat diet islets1

High Fat Diet Islets

  • Condition scores significantly differ, p-value: 8.5*10-3

  • Significantly enriched for serine-type endopeptidase activity, p-value: 3*10-12

  • Enriched for regulation by Trypsin GTF, p-value: 3*10-14


High fat diet islets2

High Fat Diet Islets

  • Module #41

  • 58 probes, 45 Entrez genes

  • Two outliers


Acknowledgements

Acknowledgements

UNIL CBG:

Zoltán Kutalik

Micha Hersch

Aitana Morton

Diana Marek

Barbara Piasecka

Bastian Peter

Karen Kapur

Alain Sewer

Toby Johnson

Armand Valsessia

Gabor Csardi

Sascha Dalessi

KU Leuven:

Leentje van Lommel

Frans Schuit

Thanks to EuroDia!

http://serverdgm.unil.ch/bergmann


High fat diet islets3

High Fat Diet Islets

  • Serine-type endopeptidase activity, GO molecular function category


High fat diet islets4

High Fat Diet Islets

  • Intersection of module #41 and “Serine-type endopeptidase activity”, GO molecular function category


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