2024/25 Taught Postgraduate Module Catalogue

OGDS5301M Extended Data Analysis Topics

30 creditsClass Size: 150

Module manager: Dr James Poulter
Email: J.A.Poulter@leeds.ac.uk

Taught: 1 May to 31 Aug, 1 Nov to 28 Feb View Timetable

Year running 2024/25

Pre-requisite qualifications

Students are required to meet the programme entry requirements prior to studying the module.

Module replaces

None

This module is not approved as an Elective

Module summary

This module will give students an opportunity to analyse large datasets in an independent manner in order to answer a research question of their design. This will cover analysis of a range of data types and analytical techniques, for example germline DNA or RNA sequencing. Students will need to undertake 2 separate projects to complete the module. The initial analysis of the dataset will be guided through a series of set questions and supporting discussions after which the student will be allowed to choose from a range of research avenues to complete the project.

Objectives

The module will provide students with the opportunity to undertake extended data analyses in areas aligned to medical genomics. The extended data analysis will expose the students to the application of the methodology learnt through the previous modules. The students will gain experience of working independently to plan and undertake two research questions using a number of different datasets across a range of data types and traits. The background knowledge required to analyse and understand the data analysis will be provided in earlier modules. The module will also provide an opportunity for students to write up their research findings using scientific language.

Learning outcomes
On successful completion of the module students will be able to

1. Plan and execute a data project to test a hypothesis from a research question to completion in an area of medical genomics and analytics related to RNA and DNA.
2. Analyse DNA and RNA data using appropriate methods and statistical techniques.
3. Interpret, critically discuss and draw conclusions from the DNA and RNA data generated.
4. Prepare a report of the research undertaken.

Skills outcomes
Subject specific skills in data analysis.
Scientific writing - required for writing up the coursework.

Syllabus

Indicative content for this module includes:

1. Review of research methods
2. Data Exploration
3. Research questions and hypotheses
4. Data Analysis
5. Research review I
6. Research review II

Teaching methods

Delivery type	Number	Length hours	Student hours
Discussion forum	12	1.00	12.00
Tutorial	12	1.00	12.00
Independent online learning hours			276.00
Private study hours			0.00
Total Contact hours			24.00
Total hours (100hr per 10 credits)			300.00

Private study

Students will be provided with pre-prepared teaching and learning resources which scaffold learners to achieve learning outcomes to facilitate initial analysis of their chosen datasets (independent online learning). This will take them through exploration of the data, quality control and initial analysis prior to the student undertaking further independent analysis of their data.

Students will be required to choose from a range of further analysis topics related to their data in which they should undertake independent analysis. The student is expected to use the private study time to undertake this analysis and write up their results with critical analysis from the literature as would be expected for a scientific manuscript.

Opportunities for Formative Feedback

The individual webinar tutorials and asynchronous and discussion forums provide opportunities for formative feedback from peers and tutors.

Student will be given the assessment at the start of each 8 week block and will be provided with opportunities to ask questions to teaching staff before starting on the assignment.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Project	Project coursework 1 (DNA)	50.00
Project	Project coursework 2 (RNA)	50.00
Total percentage (Assessment Coursework)		100.00

The assessment of the module will be the write up of the two extended data analysis. This will include both the guided and independent questions. To achieve LO1-3 students must pass both reports independently, therefore there is no compensation between the two assessments. If one report is failed, to achieve the module credits students will need to resit the failed component of the module assessment and the module mark will be capped at a pass.

Reading list

The reading list is available from the Library website

Last updated: 19/11/2024

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