2018 PSU Bootcamp on Reproducible Research
June 18-21, 2018
DAY 1 TOP
Day 1: Perspectives on Data Reproducibility
Schedule
8:45 - COFFEE AND LIGHT BREAKFAST
9:00-9:30 - Wilfried Guiblet and Monika Cechova: Introductions.
9:30-10:15 - Cooduvalli Shashikant: Is there a reproducibility crisis?
10:15-10:35 - COFFEE BREAK
10:35-11:20 - James Broach: “10% of the time, it works every time” - Recognizing sloppy science
11:20-12:05 - Keith Baggerly: http://videolectures.net/cancerbioinformatics2010_baggerly_irrh/
12:05-1:15 - LUNCH
1:15-2:00 - Cheryl Keller: It’s a Mad, Mad, Metadata World
2:00-2:45 - Molly Hall: Quality control is essential to ensuring reproducibility in genotype and non-genetic data
2:45-3:30 - Vasant Honavar: Computational reproducibility and data sharing
3:30-3:50 - BREAK
3:50-4:05 - Aswathy Sebastian: An example of reproducibility incident
4:05-4:50 - Instructions by Shaun Mahony and TAs to Tuesday's sessions
Videos
Reading Materials
Software Installation
DAY 2 TOP
Day 2: Software carpentry and reproducible data analysis
Schedule
The basics of computational reproducibility: version control, documentation, automation.
Instructor: Dr. Shaun Mahony, Assistant Professor, Biochemistry & Molecular Biology
- 8:45 - 9:00 - Coffee and light breakfast
- 9:00 - 9:45 - Best Practices in Scientific Research
- 9:45 - 10:30 - Shell scripting basics
- 10:30 - 10:50 - Coffee break
- 10:50 - 12:00 - Shell scripting (continued) and interacting with a computing cluster
- 12:00 - 1:30 - Lunch
- 1:30 - 3:00 - Git basics
- 3:00 - 3:20 - Coffee break
- 3:20 - 5:00 - Github for team projects
Class Material
Install software
Presentation
- Software carpentry and reproducible data analysis by Shaun Mahony
- Using GitHub for team projects by Prashant Kuntala
Lesson
Best Practices for Scientific Computing
- Best Practices in Scientific Research
- Best Practices for Scientific Computing, PLoS Biology, Jan. 2014
Shell scripting
- Shell scripting basics
- Running scripts on a cluster (ICS-ACI)
Markdown
Git
Additional Reading Materials
Advanced Bash scripting
Make
- Automation with make
- Snakemake: a different kind of automation
Alternatives to Git/GitHub
Alternatives to Markdown
- Asciidoc and Asciidoctor: a different type of text markup
DAY 3 TOP
Day 3: Proper statistical inference, effective plotting and reproducible reporting
Schedule
Proper statistical inference, effective plotting and reproducible reporting
Instructor: Dr. Qunhua Li
Videos
Reading Materials
DAY 4 TOP
Day 4: Essential pieces of reproducibility - Conda, Jupyter, Galaxy, Blogs
Monika Cechova, Anton Nekrutenko | biomonika@psu.edu, anton@nekrut.org
Agenda
- 9:00 - 10:30 Conda and BioConda
- 10:30 - 10:50 Coffee Break
- 10:50 - 12:00 Intro to Jupyter
- 12:00 - 1:30 Lunch break
- 1:30 - 3:30 RNAseq with Galaxy and Jupyter
- 3:30 - 3:50 Coffee Break
- 3:50 - 5:00 Blogging with GitHub (and possibly Hugo)
Tutorials and Reading
- Conda
- BioConda
- Galaxy Training Network
- Cornell RNAseq tutorial
- Galaxy RNAseq
- Galaxy USA
- Galaxy EU
- Jupyter
- HUGO
DAY 5 TOP
Workshop on emerging methods for sequence analysis
For those that registered for the workshop, information is available at
GENERAL INFORMATION TOP
Organizers
Course location, hours, requirements
- Boot camp will be held June 18-21; 8:45-5PM in 107 Business Buildings
- Breakfasts and lunches are planned. Participants are on their own for dinners.
Please contact the organizers for registration or other bootcamp related issues:
- Dr. Cooduvalli Shashikant, Co-Director, Bioinformatics and Genomics Program Option:
css13@psu.edu
Instructors:
- Shaun Mahony mahony@psu.edu
- Qunhua Li qunhua.li@psu.edu
- Anton Nekrutenko anton@bx.psu.edu
Teaching Assistants
- Wilfried Guiblet wmg133@psu.edu,
- Monika Cechova biomonika@bx.psu.edu,
Funding and Support
The boot camp is organized by the Computation, Bioinformatics and Statistics Predoctoral Training Program at Penn State supported by the NIH T32 program. The boot camp is funded by participating colleges at Penn State.
The boot camp was first conceived and supported in Jun 2016 by the Administrative Supplement to NIGMS Predoctoral Training Grants (PA-15-136)