Introduction to Biological Network Analysis and Visualization with Cytoscape Part 2

1. Introduction to Biological Network Analysis and Visualization with Cytoscape Keiichiro Ono Cytoscape Core Developer Team UC, San Diego Trey Ideker Lab / National Resource for Network Biology 5/12/2016 The Scripps Research Institute Lecture 2: Reproducible Workﬂows with Jupyter Notebook

2. Lecture slides are available here: http://www.slideshare.net/keiono

3. Agenda • Lecture 1:    Introduction to Biological Network Analysis and Visualization • What is the beneﬁts of biological network analysis and visualization? • Introduction to Cytoscape • Preview of Lecture 2: cyREST • Lecture 2 (Today):    Reproducible Analysis & Visualization • Introduction to Jupyter Notebook • Create a reproducible network visualization workﬂows with Python

4. Review of Lecture 1 - Network analysis / visualization is a powerful method to get biological insights from your screening result - Cytoscape is the de-facto standard tool to perform this type of analysis

5. Review of Lecture 1 -Core features of Cytoscape -Navigation (Pan/Zoom/Select) -Network / Table Data Import -Automatic Layout -Visual Style

6. Recap Cytoscape Session File — for sharing results But what about process?

7. Reproducibility

8. http://www.the-scientist.com/?articles.view/articleNo/43632/title/Get-With-the-Program/ https://theconversation.com/how-computers-broke-science-and-what-we-can-do-to-ﬁx-it-49938http://www.nature.com/nature/journal/v483/n7391/full/483531a.html Reproducibility …it’s a known issue

9. Problems - Reproducibility of biological research, especially for in vivo/vitro experiments, is a hard problem - But this is true even for in silico analysis! - OS version - Revision of scripts - Data analysis software versions - Version of data ﬁles - Command line parameters written on a paper napkin - “Black magic” only a grad student knows - This is something we need to ﬁx, using latest technologies and best practices

10. Typical Workﬂow

11. Data Preparation Analysis Visualization

12. Data Preparation

13. Data Preparation - Cleansing - Normalization - Missing values - Corrupted values - Reformat - Conversion

15. Analysis

16. Analysis - Filtering - Standard graph statistics - Density - Betweenness - Centrality - Clustering - Community Detection - GO enrichment analysis

18. Visualization

19. Visualization - Mapping - Data points to visual variables - Layout - For graphs: - Force-directed - Tree

23. Cytoscape for Interactive Visualization Python for Data Manipulation / Analysis

24. Lab Notebook for in silico Experiments

25. Interactive Command-Line + Markdown-based Documents

26. IPython Notebook? Jupyter?

27. IPython Notebook Notebook UI + Python Kernel Jupyter Notebook UI + Language Kernel (R/Julia/etc.)

28. Language-Agnostic - From next version (4.x), Python Notebook will be an implementation of Jupyter - You can switch to other language kernels - In this lecture, we will use Python, but you can use language of your choice to control Cytoscape

29. Question • Cytoscape is a desktop application • Point & click GUI operation • Easy to use, but how can we make our workﬂow reproducible?

30. REST

31. What is cyREST? - Platform-independent, RESTful API module for Cytoscape - Means you can access basic Cytoscape data objects programmatically - Now it’s a Cytoscape Core feature! REST

32. Interactive Data Analysis Environments In-House Databases External Computing Resources - Graph Layout - Statistical Analysis - Data Pre-processing RStudio - NumPy - SciPy - Pandas - NetworkX IPython Notebook File / Code Hosting ServicesPublic Data Repository PSICQUIC Services EBI RDF Platform Other Bioinformatics Web Applications / Services - igraph - rCurl Command Line Tools > sed > awk > grep > curl Web Browsers Data Repository & Collaboration Service Data Bus (Internet) Your Workstation Cytoscape App Store Cytoscape Desktop Apps Core REST

33. REST Cytoscape 3.1+ Clients POST PUT DELETE GET How cyREST Works

34. Mapping Cytoscape API to HTTP Methods Create Read Update Delete Cytoscape Operations POST GET PUT DELETE HTTP Methods

35. Get full network with unique ID 52 as JSON GET http://localhost:1234/v1/networks/52

36. http://localhost:1234/v1/networks/52

37. Language-Speciﬁc Shims For Python For R

38. REST

39. REST Lab notebook to record your workﬂow Make Cytoscape controllable via scripts Manage multiple versions of your notebooks and other scripts

40. - - Two Google Groups - cytoscape- discuss@googlegroups.com - cytoscape- helpdesk@googlegroups.com - ANY question is OK! Getting Help

41. Further Readings

42. Further Readings • My presentation slides • http://www.slideshare.net/keiono • cyREST web sites • http://apps.cytoscape.org/apps/cyrest • https://github.com/idekerlab/cyREST/wiki • py2cytoscape — https://github.com/idekerlab/ py2cytoscape

43. 2016 Keiichiro Ono kono@ucsd.edu

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