This article is intended to help you get started with your first digitalMLPA™ experiments. The sections below contain an overview of the most important resources, and offer a suggested reading order.
Step 1: Understanding digitalMLPA
Watch the first short video below for an overview of the digitalMLPA technique and its advantages. Watch the second video below to get familiar with the technical principle of digitalMLPA, or read this textual explanation instead. For a more in-depth look into the technique and its advantages, you can also watch the on-demand webinar digitalMLPA: Where MLPA Meets NGS (25 min).
Step 2: Experimental setup
Make sure to review the digitalMLPA General Protocol in detail before starting. The protocol contains important information about things like validation, sample selection, instrument settings and critical experimental steps. It is very important to follow the protocol exactly, as deviations may lead to unreliable results.
The protocol also contains a list of everything that you need to set up a digitalMLPA experiment. This includes things like a thermocycler with a heated lid, a supported Illumina sequencer, ultrapure water and standard laboratory consumables. To get an idea of the number of samples that can be analysed in a single sequencer run, see our sample number calculator.
Step 3: Data analysis software
Correct data analysis is a critical step in any experiment, but especially so for the wealth of data produced by a single digitalMLPA experiment. Our free digitalMLPA analysis software, Coffalyser digitalMLPA™, has been designed specifically for digitalMLPA, and helps you get the most out of your data. For a general overview of the software, see this web page. Download Coffalyser digitalMLPA here.
Read the user manual for help setting up your first experiment. If you want to get an idea of the software and the output it generates, you can analyse one of our data demo sets.
Step 4: Quality control
Proper assessment of the quality of your data is critical for reliable results. Coffalyser digitalMLPA performs a large number of quality checks automatically. Many of these checks are based on the quality control probes that are present in every digitalMLPA probemix, which can help detect all kinds of experimental issues. The digitalMLPA General Protocol contains more information about the quality control probes in digitalMLPA probemixes.
Step 5: Result interpretation
If the data passed the quality checks in Coffalyser digitalMLPA, you can continue with the interpretation of the results. Coffalyser digitalMLPA indicates which probes were found to have ratios different from the reference sample population. Read the user manual for more information about this.
More information
You can search or browse our help centre for answers to frequently asked questions.
If you prefer to learn in a more classical setting, you can consider attending one of (virtual) workshops or webinars. More information about the contents and schedule of our workshops is available in our events overview.
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