In this course, students will analyze eukaryotic High Throughput Sequencing (aka "Next Generation Sequencing") data. Students will carry out a research project in small groups, have weekly lab meetings, and write lab reports.
Note that this course counts as Writing Intensive (department) but does not count toward Experiential Learning. However, if you do well in the course, absolutely feel free to discuss with the instructor potential research project that might count.
Students taking this section must have permission of instructor.
| Texts: | None needed |
| Meetings: | Lecture MW 11-11:50pm, location TBD (**) |
| Workshop Th 9:30-11:20am, Zoom |
| Instructor: | Michael Osier |
| Office: | 08-1338 |
| Instructor Schedule | Online |
| Contact: | mvoscl@rit.edu |
Under certain circumstances, the instructor may have to alter course requirements, assignment deadlines, and grading procedures; and the university may have to alter the academic calendar.
| Monday | Wednesday | Thursday | Writing due | |||
|---|---|---|---|---|---|---|
| Week 1 | Jan 12 | Introduction, Finding data | HTS basics: technologies and analysis, including readings | Unix/Linux command line | None | |
| Week 2 | Jan 19 | No class | HTS basics | Trapnell paper | Design analysis flowchart | |
| Week 3 | Jan 26 | Assembler readings | Start Trapnell data set - quality control | Project picking, Trapnell QC | First and second picks with justification (due week 4 Monday) | |
| Week 4 | Feb 2 | RNASeq readings | Trapnell data set - QC debrief and alignment | Weekly reports | ||
| Week 5 | Feb 9 | Composite structures readings | Trapnell data set - Alignment debrief and differential expression | |||
| Week 6 | Feb 16 | Barcoding readings | First stage analyses - Quality control | |||
| Week 7 | Feb 23 | eDNA and scRNASeq readings | ||||
| Week 8 | Mar 2 | First stage analyses - Quality control | ||||
| Week 9 | Mar 9 | Spring Break | Optional weekly report | |||
| Week 10 | Mar 16 | Second stage analyses - assembly/alignment | Second stage analyses - assembly/alignment | |||
| Week 11 | Mar 23 | Variant callers and missing genes readings | Weekly reports | |||
| Week 12 | Mar 30 | Third stage analyses - differential expression | Third stage analyses - differential expression and visualization | |||
| Week 13 | Apr 6 | Long read technologies readings | Third stage analyses - differential expression and visualization | Weekly report; Final paper draft 1 - outline | ||
| Week 14 | Apr 13 | Microbiome and epigenetics readings | Third stage analyses - differential expression and visualization | Weekly report; Final paper draft 2 - half of prose/figures | ||
| Week 15 | Apr 20 | Cleanup/bonus analyses | Cleanup/bonus analyses - SNP calling, create transcriptomes, etc. | |||
| Week 16 | Apr 27 | Cleanup/bonus analyses | Exam week activity | |||
| 10 weekly lab reports | 3 pts each x 10 = 30 pts total |
| 3 Trapnell data set Analyses | 10 pts each x 3 = 30 pts |
| Participation in First stage Analysis | 30 pts |
| Participation in Second stage Analysis | 30 pts |
| Participation in Third stage Analysis | 30 pts |
| 3 Final Paper Drafts | 2 pts each = 6 pts |
| Final Paper | 24 pts |
| Two peer evaluations | 10 pts each = 20 pts total |
| Total | 200 pts |
|---|---|
| Bonus: bonus analysis for project | 20 pts |
| Total available bonus | 20 pts |
| A | [190-200] |
| A- | [180-190) |
| B+ | [173.4-180) |
| B | [166.7-173.4) |
| B- | [160-166.7) |
| C+ | [153.4-160) |
| C | [146.7-153.4) |
| C- | [140-146.7) |
| D | [120-140) |
| F | <120 |
Each project will use real HTS data. Student form teams and pick one project during Week 3. Students will spend the rest of the semester analyzing this data set.
For each project, there may be trees of primary, secondary, and tertiary analysis steps, which are dependent on each other. For example, any Secondary Analysis will be dependent upon having a Primary Analysis that was completed correctly. Completion of more than three levels of analysis can result in bonus points! Be sure to ask the instructor well in advance if you wish to carry out the additional work to verify that it is appropriate.
Participation for each step of analysis will be graded for elements such as completeness, choice of analysis method, appropriate parameter choice, demonstration of active participation, and regular online communications through the myCourses Discussion groups. Individual participation, including full participation in all class sessions, will also be observed and incorporated.
Readings are due before the lecture meetings of that week. These readings are intended both to acclimate you to the topic of the week, and serve as discussion for that week. All papers should be available through myCourses, although some are linked out. In no case should you have to pay for any articles!
Over the semester, students must submit individual lab reports for 10 out of the 12 available weeks, counting the project choice. Reports must be 3/4 to 2 single spaced pages for undergraduates, or 1 to 2 pages for graduate students, submitted to the correct myCourses dropbox before the Thursday meeting. Reports must include the following elements:
A final paper written by the group, explaining your work, in a typical journal format, is due submitted to the myCourses dropbox before the end of the last day of classes (Monday, April 27th, 11:59pm). No late papers will be accepted.
Part of a draft, written by the group, is due during Weeks 13 through 15 on the following schedule. Drafts must be submitted to the appropriate myCourses DropBox before Thursday workshop. Each draft is worth 1% of your final grade, for a total of 3%. No late drafts will be accepted for a grade. For drafts, color your individual text in a color unique to you among your group. You must use MS Word, LibreOffice, or OpenOffice. Word is available from the COS computer labs and the others are free. Be sure to include one comment at the start of the draft with your full name so that your revision color can be identified.
Unless written permission is granted by the faculty member, or a specific accommodation has been approved by the Disability Services Office, students are prohibited from recording lectures or presentations.
For the first offense, anyone caught plagiarizing or otherwise cheating will receive a 0 (zero) on the assignment, and be referred to the Head of the School of Life Sciences. In the event of a second offense, the student will receive an "F" for the course. Duplicate submissions or excessive patchwriting will also receive a grade of 0 (zero) for the assignment. In the case of especially egregious offenses, the instructor reserves the right to assign a grade of "F" for the course, as per RIT policy.
If you have any questions about whether or not something constitutes plagiarism and/or cheating, please ask the instructor in advance.
Artificial Intelligence (AI) may not be used in this course except for the exploration of topics. Among other things, it may not be used for writing or drafting papers/reports. You may use it to get advice on how to do an analysis, for example. If you have any questions about acceptable use of AI in this course, please email the instructor immediately.
Contents last updated 10/10/25