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Development of the Next
Generation of Bioinformatic
Tools in Microbiology
Julie K. T. Pedersen
Supervisor: Mads Albertsen
...
Agenda
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
• Background
• me
• data
• Aim
• Current status
• Network
• T...
Who am I?
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
• Back from maternity leave 1. sep
• Earlier projects: pro...
Who am I?
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
• Back from maternity leave 1. sep
• Earlier projects: pro...
[ ]Human health
Salmonella
MRSA
Y. Pestis
Obesity
Dental health
Immune system
[ ]
Yoghurt
Alcohol
Salami
Sourdough
Cheese
Saurkraut
[ ]Food
[ ]Biotechnology
Wastewater
Biogas Bioplastic
Medicaments
Drinking water Enzymes
They help clean our water
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Wastewater
Some of them create problems
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Wastewater
Identification – 16S rRNA amplicon sequencing
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Wastewater
Identification – 16S rRNA amplicon sequencing
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Wastewater
OTU: Operat...
Identification – 16S rRNA amplicon sequencing
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Wastewater
[Karst et a...
Repeat over time period
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Wastewater
[Karst et al., 2016]
Time-series from Aalborg West
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
• 9 years, varying sampling frequency
...
Time-series from AquaDjurs (Fornæs)
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
• Approx. 2 times a week for hal...
Aim
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Explore microbial correlation patterns in time-series data
• Aal...
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Learning new skills with DataCamp!
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Learning new skills with DataCamp!
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Learning new skills with DataCamp!
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
[ ]
Using my new skills!
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
  
Using skills - demo
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
What is correlation?
Are these 2 bacteria
correlated?
What is correlation?
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
r = 0.816
What is correlation?
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
R = 0.816
r = 0.816 r = 0.816
r = 0.816 r = 0.8...
What is correlation?
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Correlation Causation≠
Looking at correlations
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Step 1: Calculate a correlation matrix
Step ...
Step 1: Calculate a correlation matrix
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
A
B
C
D
Step 1: Calculate a correlation matrix
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Step 2: Build and filter a network graph
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
A
B C
D
0.82
0.87
0.37 0.96...
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
C
0.87
0.96
A
D
0.82
Step 2: Build and filter a network graph
Step 2: Build and filter a network graph
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
• Thresholds:
• OTU Count
•...
Step 3: Make it pretty and identify correlations
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
”OTU_1”
”OTU_2”
Str...
Step 4: Look at the data behind the correlation
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Yes, they are correl...
So, what’s next?
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
http://www.readwritethink.org/files/resources/inter...
So, what’s next?
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
• Real data (YEESS!)
• Can I find the troublemakers...
Follow my progress
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
Open source:
https://github.com/julieklessner
www...
Thank you!
CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
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Status seminar 31.01.17, Aalborg University

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Presentation slides from Statusseminar at Aalborg University, where i presented the master thesis work so far. Hand-in: late may.

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Status seminar 31.01.17, Aalborg University

  1. 1. Development of the Next Generation of Bioinformatic Tools in Microbiology Julie K. T. Pedersen Supervisor: Mads Albertsen CENTER FOR MICROBIAL COMMUNITIES 2017-01-31 Aalborg, Denmark
  2. 2. Agenda CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY • Background • me • data • Aim • Current status • Network • Timeseries • What’s next?
  3. 3. Who am I? CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY • Back from maternity leave 1. sep • Earlier projects: proteins and DNA • Albertsen Lab (Part of EB group) • Master: purely bioinformatic • Blog: ”Life as a master student”
  4. 4. Who am I? CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY • Back from maternity leave 1. sep • Earlier projects: proteins and DNA • Albertsen Lab (Part of EB group) • Master: purely bioinformatic • Blog: ”Life as a master student”
  5. 5. [ ]Human health Salmonella MRSA Y. Pestis Obesity Dental health Immune system
  6. 6. [ ] Yoghurt Alcohol Salami Sourdough Cheese Saurkraut [ ]Food
  7. 7. [ ]Biotechnology Wastewater Biogas Bioplastic Medicaments Drinking water Enzymes
  8. 8. They help clean our water CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY Wastewater
  9. 9. Some of them create problems CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY Wastewater
  10. 10. Identification – 16S rRNA amplicon sequencing CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY Wastewater
  11. 11. Identification – 16S rRNA amplicon sequencing CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY Wastewater OTU: Operational Taxonomical Unit [Karst et al., 2016]
  12. 12. Identification – 16S rRNA amplicon sequencing CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY Wastewater [Karst et al., 2016] Name %
  13. 13. Repeat over time period CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY Wastewater [Karst et al., 2016]
  14. 14. Time-series from Aalborg West CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY • 9 years, varying sampling frequency • Problems with settling • Filamentous bacteria
  15. 15. Time-series from AquaDjurs (Fornæs) CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY • Approx. 2 times a week for half a year • Implementing new online control
  16. 16. Aim CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY Explore microbial correlation patterns in time-series data • Aalborg West • Are there bacteria that correlate with known ”bad” bacteria, either positively or negatively? • Can we identify early warning indicator organisms? • AquaDjurs • How does the bacterial “interactome” look? • How large fraction of the bacteria interact? Writing user-friendly, interactive functions in R • How to make simplicity from complexity?
  17. 17. CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
  18. 18. Learning new skills with DataCamp! CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
  19. 19. Learning new skills with DataCamp! CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
  20. 20. Learning new skills with DataCamp! CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
  21. 21. [ ] Using my new skills! CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY   
  22. 22. Using skills - demo CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
  23. 23. CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY What is correlation? Are these 2 bacteria correlated?
  24. 24. What is correlation? CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY r = 0.816
  25. 25. What is correlation? CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY R = 0.816 r = 0.816 r = 0.816 r = 0.816 r = 0.816 [Anscombe, 1973]
  26. 26. What is correlation? CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY Correlation Causation≠
  27. 27. Looking at correlations CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY Step 1: Calculate a correlation matrix Step 2: Filter and build a network graph Step 3: Make it pretty and identify correlations Step 4: Look at the data behind the correlation
  28. 28. Step 1: Calculate a correlation matrix CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY A B C D
  29. 29. Step 1: Calculate a correlation matrix CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY
  30. 30. Step 2: Build and filter a network graph CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY A B C D 0.82 0.87 0.37 0.96 0.12 0.43
  31. 31. CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY C 0.87 0.96 A D 0.82 Step 2: Build and filter a network graph
  32. 32. Step 2: Build and filter a network graph CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY • Thresholds: • OTU Count • Correlation
  33. 33. Step 3: Make it pretty and identify correlations CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY ”OTU_1” ”OTU_2” Strong correlation between ”OTU_1” and ”OTU_2”?
  34. 34. Step 4: Look at the data behind the correlation CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY Yes, they are correlated.. r = 0.91
  35. 35. So, what’s next? CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY http://www.readwritethink.org/files/resources/interactives/timeline_2/
  36. 36. So, what’s next? CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY • Real data (YEESS!) • Can I find the troublemakers? • Do the troublemakers have followers? • Can i see any indicators using time delay • Other ways to calculate correlation • Can I find tools Open Source (R)? • Will they suggest different correlations? • Which to choose and why?
  37. 37. Follow my progress CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY Open source: https://github.com/julieklessner www.albertsenlab.org
  38. 38. Thank you! CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY

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