SAPLING: A Tool for Gene Network Analysis focusing on Psychiatric Genetics

Transcription

1 SAPLING: A Tool for Gene Network Analysis focusing on Psychiatric Genetics sapling.cshl.edu Wim Verleyen, Ph.D. Gillis Lab

2 Outline Motivation Disease-gene analysis Enrichment analysis Gene network analysis: network and algorithm User interface Experiment and method configuration Report generation

3 Motivation Disease-gene analysis User interface Report generation

4 Motivation Consistent functional interpretation of a disease gene list Traditional: enrichment analysis (what if there is no statistical significance?) Alternative: gene network analysis Provide brain-specific network data for analyzing promiscuous expression in the brain

5 Motivation GeneMANIA: Heterogeneous data resources Limited support for in-depth analysis DAPPLE: 1 data resources Supports very in-depth analysis New web application: Heterogeneous data resources In-depth analysis

6 Motivation Disease-gene analysis User interface Report generation

7 CHD8 DYRK1A ANK2 GRIN2B DSCAM CHD2 ARID1B KDM6B ADNP MED13L NCKAP1 ANKRD11 DIP2A SCN2A TNRC6B WDFY3 PHF2 WAC KDM5B POGZ RIMS1 FOXP1 GIGYF1 KATNAL2 KMT2E TBR1 TCF7L2 Disease-gene analysis Gene list: GWAS (common variants), exome sequencing (rare variants), disease-associated-genes, Gene Ontology (GO), etc. Analysis methods: Enrichment analysis: is the gene list enriched for a reference gene list. Gene network analysis method: predict function of (protein-coding) genes based on previous annotations. 1 Iossifov et al. (2014). The contribution of de novo coding mutations to autism spectrum disorder. Nature.

8 CHD8 DYRK1A ANK2 GRIN2B DSCAM CHD2 ARID1B KDM6B ADNP MED13L NCKAP1 ANKRD11 DIP2A SCN2A TNRC6B WDFY3 PHF2 WAC KDM5B POGZ RIMS1 FOXP1 GIGYF1 KATNAL2 KMT2E TBR1 TCF7L2 Network statistics Gene list Network: nodes represent genes edges represent interactions between genes node degree: # of connections of a node representation bias: node has a connection in the network

9 CHD8 DYRK1A ANK2 GRIN2B DSCAM CHD2 ARID1B KDM6B ADNP MED13L NCKAP1 ANKRD11 DIP2A SCN2A TNRC6B WDFY3 PHF2 WAC KDM5B POGZ RIMS1 FOXP1 GIGYF1 KATNAL2 KMT2E TBR1 TCF7L2 Gene network analysis method Gene list Probability function-associated-gene

10 Aggregation

11 Aggregation Aggregation of output scores of individual methods for gene function prediction.

12 Motivation Disease-gene analysis User interface Report generation

13 User A registration User interface

14 User interface A User registration B Experiment configuration Gene list CHD8 DYRK1A ANK2 GRIN2B DSCAM CHD2 ARID1B KDM6B ADNP MED13L NCKAP1 ANKRD11 DIP2A SCN2A TNRC6B WDFY3 PHF2 WAC KDM5B POGZ RIMS1 FOXP1 GIGYF1 KATNAL2 KMT2E TBR1 TCF7L2

15 User interface User registration Experiment configuration A B C Gene list CHD8 DYRK1A ANK2 GRIN2B DSCAM CHD2 ARID1B KDM6B ADNP MED13L NCKAP1 ANKRD11 DIP2A SCN2A TNRC6B WDFY3 PHF2 WAC KDM5B POGZ RIMS1 FOXP1 GIGYF1 KATNAL2 KMT2E TBR1 TCF7L2 Method configuration Network Algorithms Neighbor voting Logistic regression RankProp SGD-SVM Passive aggressive Random walk with restarts

16 User interface User registration Experiment configuration Method configuration A B C D Gene list Network CHD8 DYRK1A ANK2 GRIN2B DSCAM CHD2 ARID1B KDM6B ADNP MED13L NCKAP1 ANKRD11 DIP2A SCN2A Algorithms TNRC6B WDFY3 Neighbor voting PHF2 WAC KDM5B Logistic regression POGZ RIMS1 RankProp FOXP1 GIGYF1 SGD-SVM KATNAL2 KMT2E Passive aggressive TBR1 TCF7L2 Random walk with restarts Experiment execution

17 User interface User registration Experiment configuration Gene list CHD8 DYRK1A ANK2 GRIN2B DSCAM CHD2 ARID1B KDM6B ADNP MED13L NCKAP1 ANKRD11 DIP2A SCN2A TNRC6B WDFY3 PHF2 WAC KDM5B POGZ RIMS1 FOXP1 GIGYF1 KATNAL2 KMT2E TBR1 TCF7L2 Method configuration Network Algorithms Neighbor voting Logistic regression RankProp SGD-SVM Passive aggressive Random walk with restarts Experiment execution A B C D E Report generation

18 (B) Experiment configuration Gene list: any list of gene for which you would like to understand its generalizable properties. Experiment name: Each experiment allows you to collect analysis with different data resources and algorithms.

19 (C) Method configuration Algorithms Networks Neighbor voting RankProp Logistic regression SGD-SVM Passive aggressive Random walk with restarts DNA RNA Protein Sequence similarity (SQ) BLAST and pathogenicity Co-expression (Co) microarray bulk and single cell RNA Seq Protein-protein interaction (PPI) BioGRID, HIPPIE, I2D, IntAct, and GeneMANIA Semantic similarity (SM) Biological pathways KEGG and Reactome Disease Phenocarta Shared protein domains Pfam and InterPro

20 Heterogeneity of networks

21 Motivation Disease-gene analysis User interface Report generation

22 Report generation Enrichment analysis on the original gene list Extend gene list with novel candidate genes Performance evaluation for novel candidate genes Network visualization and enrichment analysis on extended gene list All methods finished? No Yes Consensus prediction of novel candidate genes

23 CHD8 DYRK1A ANK2 GRIN2B DSCAM CHD2 ARID1B KDM6B ADNP MED13L NCKAP1 ANKRD11 DIP2A SCN2A TNRC6B WDFY3 PHF2 WAC KDM5B POGZ RIMS1 FOXP1 GIGYF1 KATNAL2 KMT2E TBR1 TCF7L2 1 Rare variants in autism Recurrent de novo mutations for the Simons Simplex Collection (SSC) Import gene list for functional interpretation with SAPLING Full report can be found at sapling.cshl.edu Iossifov et al. (2014). The contribution of de novo coding mutations to autism spectrum disorder. Nature. 1

24 Enrichment analysis GO identifier Function Multiple test correction: Benjamini - Hochberg adjusted p-value

25 Enrichment analysis cont. GO identifier Overlapping genes between original and reference gene list Number of gene is reference gene list Number of overlapping genes

26 Network analysis: top 20 novel candidates Gene symbol Standardized ranked output score of method (neighbor voting and Phenocarta)

27 Network analysis: performance evaluation ROC curve of method (neighbor voting and InterPro) Performance comparison with reference gene lists

28 Network analysis: visualization Genes in original gene list Novel candidate genes Indirect connected genes Direct connection Indirect connection

29 Consensus prediction of novel candidates Top 20 candidate genes ROC curve for the consensus predictor

30 Conclusion User-defined network analysis and enrichment analysis SAPLING supports a field-wide functional interpretation of a disease-gene list Find sample reports at sapling.cshl.edu for ADHD and synaptic interactions Please do not hesitate to contact us if you would like to suggest any new features

31 Acknowledgements Gillis Lab at CSHL Jesse Gillis Sara Ballouz Megan Crow IT crowds at CSHL Supported by a grant from T. and V. Stanley