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AVS 454-554: DNA Sequencing Analysis Lab


This course will take students from raw DNA sequencing data through quality assurance, through to data interpretation, statistical analysis, and presentation of the results as a mock scientific article.  A background in microbiology, microbial ecology, or genetics would be beneficial.  No programming or data analysis experience is required. Students who are performing research may bring their own sequencing data to process in class.  Students will become familiar with command-line programs and basic computer programming techniques; understand bioinformatics methods such as quality trimming, assembling contigs, sequence alignment, using reference databases, and statistical comparisons; gain hands-on experience in bioinformatic analysis of DNA sequences using the R platform and its packages; primarily, DADA2, phyloseq, vegan, ggplot2; and be able to apply the knowledge gained in class to other sequence types and programs. Students may bring their own data, or some can be provided.  AVS 454 and 554 cannot both be taken for credit.

Student Learning Objectives:

After completion of the course, students will be able to:

Taught annually in the fall semester


** Syllabus is subject to change.


Class participation: Students are expected to participate in discussions in class.  I strive to create inclusive discussions, but if students still find it challenging to participate please notify me and I will alter the discussion format as needed.

Late Assignments: Assignments will be accepted after deadlines, but you might not receive feedback.  Assignments will not be accepted after the last day of the semester.

Note on authorship: If you are pursuing a manuscript for publication in this class, the work you generate is your intellectual property.  I do not expect to be an author on your manuscript, or to have ownership over any materials you generate.  I would like me/the class to be mentioned in the Acknowledgments section.  I will help you facilitate authorship roles with the full research team (i.e. the people that generated these data).

Classroom policy: Supporting inclusion and community in science is an active process that involves both invitation, and support to ensure that the scientific community is and remains an equitable and inclusive place. Students are expected to conduct themselves in a professional and courteous manner, and to abide by University policies.

Campus Policies: “The University of Maine is an EEO/AA employer, and does not discriminate on the grounds of race, color, religion, sex, sexual orientation, transgender status, gender expression, national origin, citizenship status, age, disability, genetic information or veteran’s status in employment, education, and all other programs and activities.” Follow the links for more information.

Academic Honesty Statement*   

Students Accessibility Services Statement*

Course Schedule Disclaimer*

Observance of Religious Holidays/Events*

Sexual Discrimination Reporting (Long)*

Sexual Discrimination Reporting (Short)*

** I am a “mandatory reporter”.  If you disclose something to me, I am obligated to disclose to the relevant campus Title IX office.  This includes information revealed in class assignments.

Note: this course was previously developed as a special topics precursor, taught Spring 2020; AVS 590: Special Topics in DNA Sequence Analysis Lab

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