Quantitative PCR
This is a template which you can use to help get you started on the wiki submission. It is just intended as a guide and you may modify the structure to suit your project.
Contributors
- Name and what department each person was in.
- Student or staff partner?
- How was each person involved?
- What rough dates did they contribute?
- Jaroslaw Ciba, Department of Physics.
- Thomas Travis, Department of Physics.
- Marcus Essam, Department of Medicine
- Jacky Zhu, Department of Medicine
- Anabel Varela Carver, Department of Surgery & Cancer. Staff partner from October 2021.
- Joana Dos Santos, Department of Surgery & Cancer. Staff partner from October 2021.
- Jon Krell, Department of Surgery & Cancer. Staff partner from October 2021.
- Robert Kypta, Department of Surgery & Cancer. Staff partner from October 2021.
Aims & Learning Outcomes
This visualization is intended for self-study to support iBSc Cancer Frontiers Module 1 teaching (q-PCR principles, data analysis and application to an experiment involving cancer cells)
qPCR is a laboratory technique widely employed in life science related subjects. It is build upon the foundation of PCR, a technological innovation allowing exponential amplification of genetic material. qPCR (Quantifying PCR) builds directly upon this concept, while enabling researchers to monitor the quantity of genetic material in real time as they amplify, hence the name qPCR or real-time qPCR. Through the analysis of data generated by qPCR, researchers will be able to conclude the presence or absence of a gene inside samples, as well as comparing their amounts in relative terms. Its most recent usage that gained global attention was its contributions to combating COVID-19 through viral DNA testing, which is considered the most accurate test to discover a current infection even in asymptomatic individuals.
Intended Learning Outcome:
After using this visualization, students should be able to explain how changes in Ct values from a q-PCR experiment relate to changes in the numbers of copies of a gene that a cell contains (for example, a cancer cell upon treatment with a drug).
Design Overview
- What the final outcome was, how it looks, how it functions etc.
- Include graphics.
- Do not include justification or design progression, leave this for later sections.
Design Justification
Assessment Criteria
- List your cohort's assessment criteria. You may want to number the assessment criteria so you can refer to them easily later.
Education Design
- What Methods were considered to convey concepts?
- Design progression, key choices with justifications.
- How has feedback been incorporated.
Graphical Design
- How were accessibility issues considered?
- How was space used effectively?
- Design progression, key choices with justifications.
- How has feedback been incorporated.
- How is the design intuitive?
Interaction Design
- Choice of interactive element(s) that fit in organically with the visualisation [inspiration of choice might be from lecture/in-class activity or other sources] - Sliders/Buttons/Cursor (hover/click).
- Keeping accessibility of interactive elements in mind during design phase.
- Design progression, key choices with justifications.
- How has feedback been incorporated.
Progress and Future Work
- Is the design finalised?
- Which pages have been uploaded to website?
- Any ideas for future improvements.
Links
- Link to GitHub repository for code in development:
- Link to visualisation on ImpVis website (when uploaded):
- Link to Collection on ImpVis website (when created):
- Any other links to resources (Miro boards / notes pages / Google Docs etc):