1. BF528 - Applications in Translational Bioinformatics
1/19/2018

2. Instructor Introductions
Adam Labadorf
David Bray
Rachael Ivison
Kritika Karri
Marzie Rasekh
Meghan Thommes

3. Course Overview Survey course in bioinformatics
Focus on high-throughput sequencing data, tools, and techniques
Focus on practical skills
Group work simulates real-world collaborative environment

4. Course Goals
Survey current bioinformatics techniques in translational studies
Give you hands-on experience working with high-throughput biological data and tools
Read and understand papers that use bioinformatics in translational studies
Develop shared vocabulary between biology and computation

5. Prerequisites Molecular and cell biology
BF527, BE505/605 or equivalent
Good-to-haves:
Basic statistics knowledge
Programming/linux cluster experience
But don’t panic...

6. Course Organization http://bf528.readthedocs.io
Wed/Fri 2:30-4:15 SED 208
Semi-flipped paradigm
Online content limited to ~1 hr/class
Class period split into two segments:
Lecture or discussion of online material
Project group meeting and discussion

7. Course Organization cont’d
Students assigned into groups of 4
4 projects over the course of the semester
No homeworks
No exams

8. Schedule of Topics Class Day Date Topic Project Out/Due Lecturer 1 Fri
Jan 19
Introduction
Adam 2
Wed
Jan 24
Computational Skills Primer
Kritika 3
Jan 26
Genomics, Genes, and Genomes 4
Jan 31
Array Technologies 5
Feb 2
2nd Gen Sequencing
Marzie 6
Feb 7
Sequence Analysis 1 - WGS/WES 7
Feb 9
Genomic Variation and SNP Analysis 8
Feb 14
Biological Data Formats 9
Feb 16
Databases 10
Feb 21
Sequence Analysis 2 - RNA-Seq
1/2 11
Feb 23
Biomarkers
Marc 12
Feb 28
Sequence Analysis 3 - ChIP-Seq
David 13
Mar 2
Phylogenetics
Spring Break

9. Schedule of Topics cont’d14
Wed
Mar 14
Gene sets and enrichment
2/3
Kritika 15
Fri
Mar 16
Replicability vs Reproducibility Strategies
Adam 16
Mar 21
Computational Pipeline Strategies 17
Mar 23
Computational Environment Management 18
Mar 28
Sequence Visualization
David 19
Mar 30
Microbiome: 16S
Meghan 20
Apr 4
Microbiome: Metagenomics
3/4 21
Apr 6
Metabolomics 22
Apr 11
Proteomics/Mass Spectrometry
Andrew 23
Apr 13
Single Cell Techniques 24
Apr 18
Integrative Genomics 25
Apr 20
Network Biology 26
Apr 25
Systems Biology 4
Trevor 27
Apr 27
The Future + Retrospective
Ensemble

10. Projects Assigned into groups based on experience
Groups are for the entire semester
You will reproduce published findings from published manuscripts
Each project has a full writeup

11. Project Groups Group members will play one of four roles:
Data Curator - find, download, and organize data
Programmer - process data into analyzable form
Analyst - transform processed data into interpretable form
Biologist - understand paper and biological context, help interpret results
Roles rotate for each project
Structured class time to help facilitate group work and help each other!

12. Project Group Meeting : Wednesdays
Time allotted for groups to meet and discuss progress
“Stand-up” meeting structure:
“What did I work on since our last meeting?”
“What challenges did I encounter?”
“Are there any obstacles to completing my work?”
“What will I be working on for next meeting?”
Each group will make a brief status report at the end of class

13. Project Group Meeting : Fridays
Time allotted for roles to meet and discuss progress
Similar structure to Wednesdays
Share challenges and solutions among roles
Each role group will make a brief status report at the end of class

14. Project Report Organized like a published study
Sections (primary role):
Intro - background and motivation (Biologist)
Data - data description (Data Curator)
Methods - processing and tools (Programmer)
Results - findings (Analyst)
Discussion - interpret findings (Biologist)
Conclusion (all)

15. Assessment Each project is 25% of your total grade Broken down:
Intro, Conclusion - 2.5%
Data, Methods, Results, Discussion, 20%
Stand-up participation: 15%

16. Translational Bioinformatics

17. Biology as Data Science
DNA structure published in Nature
first genetic sequence determined, protein DataBank
Sanger sequencing, first genome sequenced
PCR technique invented
Human Genome Project begun
first bacterial genome sequenced, microarray technology first described
yeast genome on a microarray, sequencing by synthesis concept established
first multicellular eukaryote sequenced
first draft of human genome
Solexa Genome Analyzer released

18. “Big” Data Single Microarray dataset: ~500Mb
Single short read dataset: ~2Gb-300Gb
Human genome reference sequence: ~2Gb
One run of Illumina instruments:
HiSeq 2500: ~1Tb
NovaSeq 6000: ~6Tb
Gene Expression Omnibus (GEO):
2014: 1,237,138 samples, ~28 Tb
2018: 2,335,694 samples, ?? Tb

19. What is Bioinformatics?
“Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data. As an interdisciplinary field of science, bioinformatics combines computer science, statistics, mathematics, and engineering to study and process biological data.”
Wikipedia

20. Conceptual History of Bioinformatics
Biological sequences digitized
Biological databases needed to store sequences
Search tools needed for databases
Tools for analyzing data from searches
Computational tools required to analyze human genome
Sophisticated sequence analysis tools enable analysis of large amounts of sequencing data
Sequencing data volume explodes, requiring new tools
And here we are

21. The Biologist’s Tools
Wet lab biologists:
Bioinformaticians:

22. Sequence: The Fundamental Datatype
Computer Science
genome assembly, homology, phylogeny
Physics
DNA/RNA/protein structure, drug prediction
Statistics
gene expression, population genetics, biomarkers
Mathematics
metabolic modeling, synthetic biology, systems biology

23. Genbank Sequences

24. Translational Bioinformatics
“Translational Bioinformatics is an emerging field in the study of health informatics, focused on the convergence of molecular bioinformatics, biostatistics, statistical genetics, and clinical informatics.”
Wikipedia

25. Workshop 0. Basic Linux and Command Line Usage
For Next Time
Assignment: familiarize yourself with the material on basic command line usage found here:
Workshop 0. Basic Linux and Command Line Usage

26. SSH and SCC SCC - Shared Compute Cluster You all have accounts on SCC
You will need an ssh client program to connect:
Mac, Linux: Terminal (included)
Windows: MobaXTerm
Connect to: scc1.bu.edu with your BU username/password
Demonstration

27. Survey Results

28. How comfortable are you with the following programming languages/concepts?

29. How comfortable are you with the following statistics concepts?

30. How comfortable are you with the following biology concepts?

31. How comfortable are you with the following bioinformatics concepts?

32. Rank the following roles that you might play in a project in order of preference

33. What do you hope to learn?

34. How do you plan to use what you learn?