1. 28. Juni 2016, BSc. Präsentation, M. Haberbusch
F O R N A V I S A tool that helps to optimize the Forna Container‘s RNA secondary structure graph generation
Max Haberbusch
28. Juni 2016, BSc. Präsentation, M. Haberbusch

2. BSc. Präsentation, 2016, M. Haberbusch
Overview
RNA Secondary Structure
RNA Secondary Structure Graph Plotting
Forna Container
Metrics
Simulation
Visualization Prototype
Advantages & Disadvantages
BSc. Präsentation, 2016, M. Haberbusch

3. RNA Secondary Structure
BSc. Präsentation, 2016, M. Haberbusch

4. RNA Secondary Structure (1)
RNA consists of nucleotides
RNA encodes the blueprint for proteins
Secondary structure describes basepairing interactions between nucleotides
Important for predicting and determining the function of RNA molecules
FASTA Format, common format for storing RNA secondary structure:
> Somesequence
; this is a random RNA sequence and its
; secondary structure
AGAUAUGUGCCGGCCUAACUCUAACGGUAAUCUUCUGUCACGACCUACGCGCCGAGGUGACCUAUAAUAGCACGCACUACGCCGUCAACUACAGAGCAUU ((((...((((( )))))))))(((((...(((....(((...(((((..(((...)))..))).)).))).)))....))))).....
BSc. Präsentation, 2016, M. Haberbusch

5. RNA Secondary Structure (2)
Different RNA secondary structure representations depending on the purpose
Undirected Graph
Mountainplot
Bonding Graph
FASTA Format
(a)
(b)
(c)
BSc. Präsentation, 2016, M. Haberbusch

6. RNA Secondary Structure as Undirected Graph
BSc. Präsentation, 2016, M. Haberbusch

7. RNA Secondary Structure as Undirected Graph
Important for identifying substructures
Substructures
Loops
Hairpins
Stems
etc.
Visualization of canonical and non-canonical interactions between nucleotides
BSc. Präsentation, 2016, M. Haberbusch

8. Examples from Google Search
BSc. Präsentation, 2016, M. Haberbusch

9. BSc. Präsentation, 2016, M. Haberbusch
Forna Container
BSc. Präsentation, 2016, M. Haberbusch

10. BSc. Präsentation, 2016, M. Haberbusch
Forna Container (1)
Force-directed graph layout algorithm for RNA secondary structure graph plotting in web browser
Implemented by the Theoretical Biochemistry Group at the Institute for Theoretical Chemistry at University of Vienna
P. Kerpedjiev, S. Hammer, I. Hofacker. "Forna (force-directed RNA): simple and effective online RNA secondary structure diagrams."Bioinformatics (2015): btv372.
BSc. Präsentation, 2016, M. Haberbusch

11. BSc. Präsentation, 2016, M. Haberbusch
Forna Container (3)
BSc. Präsentation, 2016, M. Haberbusch

12. BSc. Präsentation, 2016, M. Haberbusch
Example Outputs
Friction: 0.65
Charge: -40
Chargedistance: 80
Friction: 0.65
Charge: -140
Chargedistance: 40
Friction: 0.95
Charge: -200
Chargedistance: 150
BSc. Präsentation, 2016, M. Haberbusch

13. BSc. Präsentation, 2016, M. Haberbusch
Metrics
BSc. Präsentation, 2016, M. Haberbusch

14. Nodecollisions & Linkcollisions
Backbonelink Überlappungen
Node Überlappungen
BSc. Präsentation, 2016, M. Haberbusch

15. Linklength Deviation & Looproundness
Friction: 0.95
Charge: -190
Chargedistance: 150
Friction: 0.65
Charge: -40
Chargedistance: 80
Linkcollisions: 0
Nodecollisions: 0
Linklength Deviations: 6.5
Loop Roundness: 0.77
Linkcollisions: 0
Nodecollisions: 0
Linklength Deviations: 1.48
Loop Roundness: 0.22 vs
BSc. Präsentation, 2016, M. Haberbusch

16. BSc. Präsentation, 2016, M. Haberbusch
Looproundness
BSc. Präsentation, 2016, M. Haberbusch

17. BSc. Präsentation, 2016, M. Haberbusch
Simulation
BSc. Präsentation, 2016, M. Haberbusch

18. BSc. Präsentation, 2016, M. Haberbusch
Simulation
BSc. Präsentation, 2016, M. Haberbusch

19. BSc. Präsentation, 2016, M. Haberbusch
Sampling
Friction: [0.3 ; 0.95] with step size of 0.05
{0.3, 0.35, 0.4, …, 0.95}
Charge: [-30 ; -200] with step size of 10
{-30, -40, -50, …, -200}
Chargedistance: [30 ; 150] with step size of 10
{30, 40, 50, …, 150}
Basic quantity:
BQ = friction x charge x chargedistance
|BQ| = 3276 combinations
Random sampling:
1000 combinations, randomly picked out of the basic quantity
BSc. Präsentation, 2016, M. Haberbusch

20. BSc. Präsentation, 2016, M. Haberbusch
Random Sampling
Why?
Clutter Reduction (Visualization)
1000 points vs 3276 points per structure
Runtime Reduction (Simulation)
Basic quantity: 3276*100*5s= 19days
Random sample: 1000*100*5s= 6days
File size reduction (Simulation Results)
Literature
G. Ellis, Random Sampling as a Clutter Reduction Technique to Facilitate Interactive Visualisation of Large Datasets (2008)
BSc. Präsentation, 2016, M. Haberbusch

21. BSc. Präsentation, 2016, M. Haberbusch
Simulation
1000 parameter combinations per structure
Currently 74 structures
BSc. Präsentation, 2016, M. Haberbusch

22. Visualization Prototype
BSc. Präsentation, 2016, M. Haberbusch

23. Advantages & Disadvantages
BSc. Präsentation, 2016, M. Haberbusch

24. BSc. Präsentation, 2016, M. Haberbusch
Advantages
Allows quickly determining optima via pareto view
Identifying the distribution of simulation results
Understanding the performance of specific parameter combinations on different structuresizes
Identify input parameter trends
Comparing the quality of the graph regarding two metrics
Testing and comparing parameter combinations directly via side by side comparison of the drawn structures
BSc. Präsentation, 2016, M. Haberbusch

25. BSc. Präsentation, 2016, M. Haberbusch
Disadvantages
Just two metrics in the visualization
Only three input parameters in the visualization
No multiple point selection for better comparison
No statement on the stability of the algorithm
Performance (loadtimes)
Difficult/unable to identify combinations in the input parameter scatter plot
Red green blue coding problematic regarding colorblindness
BSc. Präsentation, 2016, M. Haberbusch

26. BSc. Präsentation, 2016, M. Haberbusch
Improvements
Parallel coordinates instead or in addition to input parameter scatter plots
Eventually color coding of points in input parameter scatter plots
Performance tuning (fine tuning of caching)
Highlighted points placed on top of others
Input parameter trends depending on structure size
Two paretoscatter side by side to compare outcomes for two different structsizes
BSc. Präsentation, 2016, M. Haberbusch

27. Thank you for your attention!
BSc. Präsentation, 2016, M. Haberbusch

28. BSc. Präsentation, 2016, M. Haberbusch
Any Questions???
BSc. Präsentation, 2016, M. Haberbusch

29. Simulation Workflow (1)
rsampling.php to generate N random parameter combinations
rstructuress.php to generate N random RNA sequences with different length in FASTA-format
RNAFold from Vienna RNA Package to generate the secondary structures
startsimulation.sh to run the simulation
BSc. Präsentation, 2016, M. Haberbusch

30. Simulation Workflow (2)
combinations.json
structures.struct
CGCUUCAUAUAAUCCUAAUGACCUAU
((..((....)).(((....))).))
[…]
./startsimulation.sh combinations.json structures.struct simulationresults
BSc. Präsentation, 2016, M. Haberbusch

31. Simulation Workflow (3)
Simulation output:
Fileformat: JSON
One file per structure containing all iterations
BSc. Präsentation, 2016, M. Haberbusch

32. BSc. Präsentation, 2016, M. Haberbusch
Simulation Dataset
Structure of the dataset to load in the simulation
BSc. Präsentation, 2016, M. Haberbusch