Introduction to Biological Network Analysis and Visualization with Cytoscape Part 2
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This document provides an introduction to biological network analysis and visualization using Cytoscape, outlining the importance of reproducibility in workflows through tools like Jupyter Notebook. It discusses typical workflows involving data preparation, analysis, and visualization, and introduces CyREST as a platform-independent API for programmatic access to Cytoscape. The lecture emphasizes the need to tackle reproducibility issues in biological research and highlights resources for further learning.
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?
- 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
- 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
- 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
- 30. Question • Cytoscape is a desktop application • Point & click GUI operation • Easy to use, but how can we make our workflow reproducible?
- 31. REST
- 32. 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
- 33. 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
- 35. Mapping Cytoscape API to HTTP Methods Create Read Update Delete Cytoscape Operations POST GET PUT DELETE HTTP Methods
- 36. Get full network with unique ID 52 as JSON GET http://localhost:1234/v1/networks/52
- 38. Language-Specific Shims For Python For R
- 39. REST
- 40. REST Lab notebook to record your workflow Make Cytoscape controllable via scripts Manage multiple versions of your notebooks and other scripts
- 41. - - Two Google Groups - cytoscape- [email protected] - cytoscape- [email protected] - ANY question is OK! Getting Help
- 42. Further Readings
- 43. 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