BIOINF 3010 - Genomics Applications III
North Terrace Campus - Semester 1 - 2022
General Course Information
Course Code BIOINF 3010 Course Genomics Applications III Coordinating Unit School of Biological Sciences Term Semester 1 Level Undergraduate Location/s North Terrace Campus Units 3 Contact 12 x 1 hour lectures, 12 x 4 hour practicals Available for Study Abroad and Exchange N Assumed Knowledge GENETICS 2510 and BIOCHEM 2500 or BIOCHEM 2502 Course Description This course teaches the underlying theory and skills for design and analysis of genome sequencing/resequencing experiments and datasets. This will include variant calling and assembly. Theoretical background will cover relevant computational, statistical, and network theory, as well as the key biological processes which are under investigation. Practical analysis will involve use of relevant assembly/variant calling software, R Studio and Bash scripting and/or a compiled programming language in the context of an HPC environment.
Course Coordinator: Professor David Adelson
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning Outcomes1. Analyse a biological question in order to develop a research analysis pipeline.
2. Use a variety of publicly available data resources and software tools to perform genomic analyses
3. Implement approaches to ensure reproducibility of a research analysis use modern literate programming tools such as R Studio Notebooks.
4. Use and communicate statistical concepts to establish and communicate the reliability of genomic analyses.
5. Employ effective techniques to communicate research results to a non-bioinformatics- specialist audience.
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s)
Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
1, 2, 3, 4, 5
Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
1, 3, 4, 5
Attribute 3: Teamwork and communication skills
Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.
3, 4, 5
Attribute 4: Professionalism and leadership readiness
Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.
1, 2, 3, 4, 5
Attribute 5: Intercultural and ethical competency
Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.
Attribute 7: Digital capabilities
Graduates are well prepared for living, learning and working in a digital society.
1, 2, 3, 4, 5
Attribute 8: Self-awareness and emotional intelligence
Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.
Learning & Teaching Activities
Learning & Teaching ModesPracticals are supported by lectures that build students student’s understanding of the details of performing complete genomics analysis pipelines. Practical tasks and associated report preparation will help develop students’ capacity to perform genomics analyses and communicate analytical results to others in an effective way.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.A student enrolled in a 3 unit course, such as this, should expect to spend, on average 12 hours per week on the studies required. This includes both the formal contact time required to the course (e.g., lectures and practicals), as well as non-contact time (e.g., reading and revision).
Learning Activities SummaryThe course covers practical aspects of conducting genomics research analyses using contemporary tools such as the R statistical environment using R Studio, literate programming using R markdown notebooks and presenting analyses to clients and other researchers.
The course will involve a scaffolded development of techniques used to perform bioinformatics and statistical analyses of small genomics datasets with supporting lectures to establish an understanding of the background theory for the practical studies.
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment task Type of assessment Percentage of total assessment Hurdle Outcomes being assessed Approximate timing of assessment Practical tasks Formative and summative 100 No 1-5 Weeks 2-12
Assessment DetailPractical tasks (total of 100%)
Each practical will include an assessment task which will be dependent on the aspects of the work being performed in the practical, to be submitted at the beginning of the subsequent practical. Each report will be 1000 – 1500 words in length.
In order to allow appropriately scoped practicals that are within the capabilities of the students and that will allow adequate coverage of the material being taught, approximately 6 assessment tasks will comprise this component of the course.
Assessments for practical tasks will be returned to students within two weeks of completion of the task to allow students to incorporate assessor feedback into their learning and practice.
SubmissionIf an extension is not applied for, or not granted then a penalty for late submission will apply. A penalty of 10% of the value of the assignment for each calendar day that the assignment is late (i.e. weekends count as 2 days), up to a maximum of 50% of the available marks will be applied. This means that an assignment that is 5 days late or more without an approved extension can only receive a maximum of 50% of the marks available for that assignment.
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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