-
Introduction to live basecalling in MinKNOW
For MinION Mk1B, Flongle on MinION Mk1B, and PromethION 2 Solo, the MinKNOW software presents an option to basecall reads on the local computer. The basecalling is carried out live, as the read files are generated during a sequencing experiment.
Basecalling results are displayed in real-time in the MinKNOW user interface, and data is written out in the BAM or FASTQ file format.
-
Fast, High Accuracy and Super Accurate models and compatibilities
The MinKNOW basecallers offer three different basecalling models: a Fast model, a High accuracy (HAC) model, and Super accurate (SUP) model.
The Fast model is designed to keep up with data generation on Oxford Nanopore devices (MinION Mk1C, GridION, PromethION). The HAC model provides a higher raw read accuracy than the Fast model and is more computationally-intensive. The Super accurate model has an even higher raw read accuracy, and is even more intensive than the HAC model.
For more information about basecalling accuracy, see the Accuracy page on the Oxford Nanopore website.
A comparison of the speed of the models is provided in the table below:
The number of keep-up flow cells assumes a 30 Gbase flow cell output in 72 hours for MinION and GridION, and 100 Gbase output in 72 hours for PromethION.
-
Sources of basecalling error
There are two main errors an event detection algorithm can make:
- Insertions: when an extra base is inserted where there should not be one - typically, this means a span of raw data points that corresponds to a single set of pore contents.
- Deletions: when a base is missed out.