Hui-Min Chung University of West Florida

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Genomics at University of West Florida

Course Overview

The class was scheduled 3 hours per week, usually consisting of an hour of lecture/discussion followed by independent work time. We focused on annotating D. erecta fosmids. I intended to engage students in a “research” set-up, thus no exams were given, and all the course materials and exercises were designed to pave students’ paths of completing their fosmid annotation project, and to help them improving their communication skills. Several elements used and learnt in the GDA course are discussed below.

Implementation and Lessons Learned

Due to the school policy and the circumstance on course offering in our institute, I eventually implemented the genomics research in the courses of directed studies in the Fall 2007 and Spring 2008 semesters. In the Fall 2007 semester, I had one student working together with Chris Kay, who has previously attended the GEP TA workshop, on annotating a D. erecta fosmid. Every week, they met for at least two hours for this study, and I met each of them separately to discuss their progress. This experience helped me to know more about their learning styles, which turned out to be very helpful in designing the course material for the Spring 2008 semester. In the Spring 2008 semester, 7 students participated the directed study course, which I named  “Genome Data Analysis (GDA)”.


Use simple exercises to gradually prepare students to be familiar with the tools

Knowing what each web resource can do is critical for students’ success of annotating their fosmids. At first students often were not familiar with the resources of genomics research. It usually took them several layers of practice to use the web resources comfortably. Personally I thought the homework exercises designed by GEP might be a bit too challenging for our students, which asking them to connect many dots in one homework. Instead I used three simpler exercises in the first month of the semester to get students acquainted with the web resources (see below). After that, students were quite familiar with each other. Except one who volunteered to do the project alone, they then chose their own partners to work in pairs on the annotation projects.

Provide sessions to openly discuss annotation techniques and problems

Learning from peers usually serves well in motivating students’ learning interests. In the second month of the semester, students took turns to do progress reports, openly discussing their annotation strategies and problems encountered. In addition, a peer review practice associated with one of the course exercises enabled each student to learn another two students’ annotations. Students highly valued these opportunities to learn from their peers. I guess that psychologically students felt better of knowing other students too have some kind of problems in annotating (and writing); and, yes, it feels great to be able to offer your peers some help in their research. I felt that, it was in the second month that they finally were mentally wired with the web resources and felt comfortable to complete their projects. It also seems that they matured their annotation techniques by working on their own projects than learning from the mock exercises from the lecture part.

Prepare students challenging Genscan predicted models.

Although it was introduced in the lecture that gene models made by Genscan are not necessarily correct, students nevertheless still felt insecure on their own judgments. It is especially evident in those who were very used to obey authorities (yes, in their minds, computers do not make mistakes.) A student suggested me to come out a “find mistake” type of exercise to mentally prepare them feeling comfortable of challenging Genscan. Another student, in contrast, went to the opposite side, suggesting abandoning using Genscan completely. Personally I value using Genscan predicted models as starting points for annotations because it is convenient, and because it provides good learning lessons of critical thinking. Most of students also favored keeping using the gene models predicted by Genscan. I guess it will be helpful to have a “find Genscan mistake” type of homework exercise included in the next round of GDA directed study.

Provide additional software tools

One common scene among students’ note taking was the disorganization of DNA sequences important for their annotation. Although copying and pasting snap shots of computer screens were very helpful in their note taking, students often found it was hard to keep their DNA/peptide sequences in files that are easy to check. It is a great pity that Mac OS10.4 does not support DNA Strider, a wonderful software used in molecular biology before. I managed to find some software such as Serial Cloner for students to check if any mistake on their ORFs and to organize their data. I read in the GEP forum that the Apollo software was very helpful for viewing and editing genome annotation.

Engage students to use the Flybase website more.

I only realized in the middle of the semester that I did not emphasize enough of using the Flybase website in the lectures given in the beginning of the semester. I regret that, after all it is inevitable to use Flybase when annotating Drosophila genomes. That being said, personally I found the Flybase website is not very easy to use in a student’s or a non-fly-person’s perspective. Sometimes information appears in the Flybase is inconsistent with what shown in the Ensembl website. Nevertheless it is important for the instructor to keep update with the changes made in the Flybase website to guide students. For instance, the instructor needs to guide students what to do with the D. erecta annotated genome available in the Flybase when students are annotating the same genome.

Future Plans

Syllabus for Genomic Data Analysis

Genome Data Analysis Course Information - Spring 2008

Instructor and TA

Hui-Min Chung and Chris Kay

Class time and place

Wednesday 5:30 – 8:30 PM in building 58 computer lab


Grading

Participation in discussions, summary papers on reading 10%

First three Lab Exercises 30%

Lab Exercise 4 – a writing exercise 15%

Peer review 10%

Report on annotation (written) 20%

Report on annotation (oral) 15%


Software tools


I managed to find some software such as Serial Cloner (can be downloaded at http://serialbasics.free.fr/Serial_Cloner.html).

I read in the GEP forum that Apollo (downloaded at: http://flybase.bio.indiana.edu/static_pages/annot/apollo.html )software was very helpful for viewing and editing genome annotation.


Class schedule of Genome Data Analysis

Week Topic Notes
1 Course introduction, and survey
2 The power of BLAST & Lab Exercise 1
3 About sequence alignment & Lab Exercise 2 Lab Exercise 1 due
4 Finding genes & Lab Exercise 3 Lab Exercise 2 due
5 Annotation strategies & Claiming projects Lab Exercise 3 due
6 Discussion of Exercies; TA’s presentation & Lab Exercise 4
7 Progress discussion – Group 1 & Work on your project
8 Progress discussion – Group 2 & Work on your project
9 Progress discussion – Group 3, guidelines for peer review & work on your project Lab Exercise 4 due
10 Progress discussion – Group 4,  Discussing Lab Exercise 4 - peer review feedback Lab Exercise 4 peer review due
11 Spring break week
12 Work on your project Lab Exercise 4 2nd draft due
13 Work on your project exchange draft for peer review
14 Work on your project 2nd draft peer review due
15 Oral Presentation Week Oral presentation ppt file due
16 Submit project report, Survey, Discussion, & Pizza Project Report due




Exercises

Files for download

Lab exercise 1

Lab exercise 2

Lab exercise 3

Lab exercise 4