If you get the real data, it should look (after zooming in) something like this:
The default parameters are fine, so just press OK. If you want to do drift correction later then you should change "Output order" to "Group temporally". That will run HAWK and bring up the processed data which (after zooming in) looks like this:
And that's it for HAWK!
You now need to analyse the HAWK processed data with some sort of localisation algorithm. If you don't have any installed, then you look at our analysis of the data performed with ThunderSTORM. You can load a ThunderSTORM analsis of both the raw and HAWK processed data from the same menu. If you have ThunderSTORM installed, then go to Plugins >ThunderSTORM > Run analysis which will bring up the following dialog:
For best results check the "Multi-emitter fitting analysis" box, then press "OK". (Here we have a high degree of overlap, which is why multi-emitter fitting is necessary. Examples of HAWK combined with single emitter fitting are given in the paper.) This will take a few minutes to run. When it's done you should get the following results:
We recommend that you set a filter to remove small localisations (shown). Here are the results side by side. Left: Multi-emitter ThunderSTORM. Middle: HAWK with multi-emitter ThunderSTORM. Right: widefield data (average of the stack). You can see that in the podosome circled in the centre, the HAWK analysed data shows the circular structure which is not visible in the widefield or ThunderSTORM only analysed data.
Note that the results are shown using our reconstruction software. If you perform ThunderSTORM or QuickPALM analysis on your own data, you can load it into our reconstruction using Plugins > Cox Group > Localisation Reconstruction > Load ThunderSTORM or Plugins > Cox Group > Localisation Reconstruction > Load QuickPALM Note that ThunderSTORM will often fit single noise pixels as fluorophores. This is more likely to happen in HAWK filtered data than in standard data. Fitting to a HAWK dataset with ThunderSTORM may therefore lead to a large increase in the number of detected fluorophores. To remove these identifications, you need to filter the fitted fluorophore positions so only those with physically realistic widths are accepted.