MinKNOW Features and Run Assessment

Marta Verdugo from Oxford Nanopore Technologies is the presenter for the Nanopore Learning sessions I watched tonight. The series of videos focused on MinKNOW and setting up an experiment. Verdugo provided an overview of the MinKNOW graphical user environment. In the second video of the series, they set up a control experiment. One experiment setup step that I didn’t know about was that you can save experimental setups as “templates.” Control experiments run for six hours. Depending on the kit used, expansion options are autopopulated. Voltage can be adjusted if you are reusing a flow cell. There are also several options for barcodes. I will read about those or hover over the options to reveal descriptions. Verdugo started and ended a run to learn about the MinKNOW features. In the “Assessing your run” lesson, Verdugo explained some of the output and real-time run monitoring options. The Channel States Panel shows most pores sequencing for a good library. Verdugo noted that 50% or above active pores sequencing suggests a good library. The translocation speed graph depicts the median translocation speed and ranges. The Q score graph should be monitored for quality drop off events, for example. The bias voltage graph, Verdugo noted, will be different for new flow cells. Total reads, the N50, and number of reads per barcode are just some of the real-time data monitoring options in MinKNOW. This video is a couple of years old yet most features remain. I also keep on learning more about what some of the values and graphs may represent when it comes to monitoring a run.

graph on laptop screen
How can we use the MinKNOW output to monitor and improve sequencing runs? Photo by ThisIsEngineering on Pexels.com