BCB660 Introduction to Next-Gen Sequencing Spring 2018

Overview of next-generation sequencing data analysis including hands-on practice using computational tools to solve a variety of biological problems. Topics include: Quality Control, contamination analysis, Genome assembly, alignments, genome annotation, RNASeq, Atac-Seq, ChIP-Seq and SNP analysis. Students will be able to work at their own pace and choose topics they are most interested in learning for the majority of the course.

Prerequisite for this course is EEOB546X “Computational Skills for Biological Data” Students will be provided access to high performance computing clusters to work on the data analysis.

Course Goals:

Provide a hands-on experience in analyzing next-gen sequencing data. Students will understand various sequencing technologies and how to apply appropriate tools to analyze big data.

Intended audience:

Graduate students interested in gaining experience in ​a variety of ​high-throughput sequencing data analyses​ tailored to their needs.​

Textbook: No required textbook. Course materials and research articles will be provided and taken mainly from the Bioinformatics Workbook at https://github.com/ISUgenomics/bioinformatics-workbook/blob/master/index.md

Grading

|Points | Description| |-|-| |20| Slack, XSEDE, Github Assignment| |20| Regular expressions Assignment| |40| Project plans | |20|Alignment project|
|100|RNA-Seq project|
|400|Projects 1-4 (100 points each)|
|600 |Total|

Projects 1, 2, 3 and 4 are determined by the student and can be chosen based on their interests. The following topics are currently available to choose from:

Project plans are required for each of the four projects chosen by the students and are to be completed prior to the start of the next project time start period.

Multiple projects can be completed in each time period. However, projects must be designated as one of the four main class projects or a bonus project prior to start and cannot be changed. Class projects are out of 100 points as described above. Bonus projects are out of 25 points but have a a maximum possible points of 50, meaning that 25 extra credit points could be achieved per bonus project.

Intended Learning Outcomes:

Students are expected to gain an understanding of the importance of bioinformatic approaches in modern biological research. For each topic covered, they will understand the fundamental biological questions and be able to apply appropriate computational tools. Students will understand basic principles underlying computational approaches, realize the limitations of available tools, and be able to critically interpret results.

Late assignments

Assignments turned in late will receive a 10% reduction off of the total possible points for every day it is turned in late until 10 days after the assignment is due at which time no points will be given even if the assignment is turned in late.

Class projects

Students are required to complete projects and assignments independently but can work together to help each other by asking questions as needed while going through the provided tutorials. Projects will be recorded using markdown in a GitHub private repositories provided by the instructor to each student. Projects are expected to include an Introduction summarizing the project goals and species, Methods that include each command used to generate output used in the results, Results describing the major findings, a Discussion section that describes the meaning behind several results discovered and a Future Directions section that describes where the student would take the project from here. Figures and tables should be included in the appropriate sections. The report should reflect the students understanding beyond just getting an answer.

Students with Disabilities:

If you have a disability and require accommodations, please contact one of the instructors early in the semester so that your learning needs may be appropriately met. You will need to provide documentation of your disability to the Disability Resources (DR) office, located on the main floor of the Student Services Building, Room 1076, 515-294-6624.

Harassment and Discrimination

Iowa State University strives to maintain our campus as a place of work and study for faculty, staff, and students that is free of all forms of prohibited discrimination and harassment based upon race, ethnicity, sex (including sexual assault), pregnancy, color, religion, national origin, physical or mental disability, age, marital status, sexual orientation, gender identity, genetic information, or status as a U.S. veteran. Any student who has concerns about such behavior should contact his/her instructor, Student Assistance at 515-294-1020 or email dso-sas@iastate.edu, or the Office of Equal Opportunity and Compliance at 515-294-7612.

Religious Accommodation

If an academic or work requirement conflicts with your religious practices and/or observances, you may request reasonable accommodations. Your request must be in writing, and your instructor or supervisor will review the request. You or your instructor may also seek assistance from the Dean of Students Office or the Office of Equal Opportunity and Compliance.

After Week 7, course topics will depend on the majority interest of the class. Projects turned in by the students will be determined on individual interests based on project plans for each period.

BCB 660: Introduction to NextGen Sequencing Tentative class schedule Spring 2018