Virtual Workshop: MLPA Data Analysis and Quality Control with Coffalyser.Net

Registration for this virtual workshop is closed as the maximum number of participants has been reached. Check our event overview for other scheduled workshops.

Key information

Learning goals

• Use Coffalyser.Net analyse experiments.
• Use built-in quality control to recognise and solve common issues.
• Learn to identify and solve binning issues.
• Determine if your results are reliable.

Complete program

Data analysis and quality control with Coffalyser.Net

How to set up an experiment in Coffalyser.Net. How to troubleshoot quality control warnings. Data interpretation and data reporting.

Practical session data analysis and quality control with Coffalyser.Net

Several cases of problematic MLPA experiments are analysed by the participants and responses are recorded via virtual polling.

Preparation and required knowledge

• Prior completion of virtual workshop MLPA Raw Data Evaluation and Troubleshooting is strongly recommended as the current workshop will not go into detail about raw data evaluation and troubleshooting.
• Basic Coffalyser.Net knowledge is required; this is provided in the instruction link sent upon registration.

Practical information

• The workshop will not be made accessible in an on-demand format. However, slides can be downloaded during the event.
• A certificate of attendance is provided.
• Due to time constraints, it is not possible to bring your own data for analysis or troubleshooting. Feel free to contact us with your question.

Registration for this virtual workshop is closed as the maximum number of participants has been reached. Check our event overview for other scheduled workshops.

Other educational events

We regularly host various types of educational events. See our event overview for details.