The Kaluza software used during this online course needs a Windows operating system and cannot be downloaded to MacOS. If you do not have a Windows operating system you may still join the webinar, but you should note this in your booking comments. This will mean that you will join the course as an observer and not be able to download the software or participate in the live hands on practical, but you can still ask questions.
Pre-session tasks 1) Complete short survey (sent to all registrations 1 week prior to course date) 2) Download of Kaluza software (prior to joining the webinar if using Windows)
Process Interactive, live session delivered via Microsoft Teams with pre-session resources available on Moodle.
Online video tutorials with downloadable software, data and worksheets, supported with interactive video discussion via MS Teams. The session has a short pre-task which must be started before the webinar and involves downloading the Kaluza software to your Windows based laptop/PC.
This interactive group session will give an introduction to flow cytometric data analysis and will provide an introductory guide to the use of the analytical software Kaluza. Attendees should ideally have performed some flow cytometry already or be familiar with the use of flow cytometry for example through attendance of the ‘Introduction to Flow Cytometry Course’.
The session requires access to a working copy of the analytical software Kaluza – install and access details can be found here: Kaluza Data Analysis Software. During the session attendees will work through and analyse example data, which will be provided, and students own data can be discussed. There will also be a discussion of the appropriate statistical tools and considerations for presenting flow cytometry data.
Ability to open Flow Cytometry Standard (FCS) files in Kaluza and produce appropriate data plots including dot plots, histograms and overlays.
Understanding of the 3 principle ways Kaluza can be used to analyse and present data; protocol duplication mode, composite mode and data batches.
Appreciation of fundamental principles of data analysis required for peer review publications including, consistency of approach, data quality and ability to describe objective and subjective outputs.
Understanding of key statistics that can be extracted and how they may be used to represent data for publication.
An overview of the statistical test that can be applied to flow cytometric data.
Accessing the course
This session may be recorded. If a recording is kept of the session, then please note, that it may be made available to the wider University of Nottingham researcher community.
To access the course please follow the link below and log into Moodle using your normal username and password. You must use the link below when accessing this course for the first time as it allows you to self-enrol onto the course. Make sure that you log in to the course within two days of the course start date, after this date enrolment is disabled.
Assessment and Training Points
For specific information on how to submit the course assessment in order to receive training points/attendance badge please read the ‘assessment' section on the course Moodle page. If you have any problems or queries, please don't hesitate contact:email@example.com
To access all the course materials and the courses live streaming link visit the course Moodle page.
You will need to spend approx 30 minutes before the start of the webinar (10am prompt) downloading the Kaluza software onto your Windows laptop/PC (please note the software does not run on MacOS). Depending on your internet speed/PC/laptop this could take longer, so please plan accordingly. If you encounter problems you can join the webinar to seek advice from the tutor, but this task must at least be attempted before the webinar.
Please visit course's Moodle page in advance of the session to familiarise yourself with the content: The moodle page is accessible below.