| Unit name | Omics |
|---|---|
| Unit code | BIOLM0031 |
| Credit points | 10 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Barker |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
Scientific programming, Statistics and R. |
| Units you must take alongside this one (co-requisite units) |
None. |
| Units you may not take alongside this one |
N/A |
| School/department | School of Biological Sciences |
| Faculty | Faculty of Life Sciences |
This unit will introduce students to the theoretical and practical aspects of statistical approaches to analysing biological data. These include the design of analyses and use of computational tools to analyse omics data. The students will have the opportunity to plan, develop and implement their own analyses to answer a wide variety of biological questions using omics data.
The aim of this unit will be to:
1. Provide students with a detailed understanding of the concepts behind designing and performing omic analyses.
2. Provide students with the skills required to use and interact with the pieces of software require to perform such analyses.
The Learning Outcomes (LOs) for this unit are:
A: Knowledge and Understanding:
1. to understand the theory, rationale and limitations of `omics experiments.
2. to develop knowledge on the different data types from different omics experiments and how these data can be manipulated and exploited.
3. Develop l mindset of comparing software choices and run parameters by applying appropriate metrics, i.e. treating analysis pipelines as experiments.
B: Intellectual Skills/Attributes:
1. The ability to identify the best software pipeline for a specific problem and install software as required in a local environment.
2. The ability to write and troubleshoot job scripts to run software in an HPC environment.
3. Be able to interpret the output of data manipulation software by extracting appropriate metrics of success and comparing these using appropriate statistical and data visualization methods.
C: Other Skills /Attributes (Practical/Professional/Transferable):
An approach and mindset which will enable students to:
1. Design and analyse robust experiments in areas outside of `omics or biology
2. Integrate new software and methods into their future work whilst retaining overall integrity of and confidence in their analyses and findings.
3. Be able to write reports/publications which accurately and concisely convey their findings to others.
The unit will be delivered through a mixture of short lectures followed by individual exercises with computers. Blackboard will be used to engage students with the unit content.
A summative computer assessment will consist of a final computer task integrating most of the learning objectives.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. BIOLM0031).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the Faculty workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an
assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
