Therefore, it is very essential to develop effective and accurate tools for identification of prophages. DBSCAN-SWA, a command line software tool developed to predict prophage regions in bacterial genomes, running faster than any previous tools and presenting great detection power based on the analysis using manually curated prophages.
The source code is written by python3. Among these, Prokka requires installtion by users. First, please install the following python packages:. DBSCAN-SWA is an integrated tool for detection of prophages, providing a series of analysis including ORF prediction and genome annotation, phage-like gene clusters detection, attachments site identification and infecting phages annotation. The python script is also provided for expert users 1.
Skip to content. Star 8. This logic is basically mapped to 2 actions, namely fetchHerePlaces and clear which are imported at the beginning of the file - which don't exist yet. So let's open actions.
This is probably the most tricky part to wrap your head around. As outlined above the actions being called in Control. The actions are now in place which subsequently have to be reduced. Please open your index. And please add the the following cases to our switch clause under placesControls in the same file to let the the reducer know what to reduce for which action:. To complete this step we have to import the controls to our application in App.
With all the changes in place you browser should update itself automatically. If it doesn't happen then simply run npm start again. You will now be able to click the buttons which should start and stop the spinner in the buttons.
If you open your network console you will also see that requests are being made and if you are using the redux developer tools you will see that your redux store has been reduced with places categories after the API call has been made. But hang on, there is yet a little work to do.. If you followed the previous step carefully you will have seen that there is a parameter in API call called in which consumes the bounding box of the map.
Well, HERE has to know where to look for places. Open your Map. We will need new map listeners which will make sure that our state gets an idea of which bounding box the user is currently looking at. And another action which has to be dispatched. I have called it doUpdateBoundingBox which takes the getBounds as an argument which is part of the Leaflet Map instance. Then we will add a new simple case to our switch clause:. However, we will have to make sure that they are plotted on the map, so let's go back there We will add a new function componentDidUpdate which is part of every React class component and will be called automatically if the state has updated - I guess you will have most likely seen this guy before.
Please add this in the class itself. You will remember the lastCall parameter of our store which we can make use of here. We basically want to know if this parameter has changed compared to the previous props. If this is the case, we know a new request has been made to the API and we can update our map with the help of addPlaces. But where to the places come from? Of course, from our redux store.
Let's connect this component with this following snippet but don't forget to remove the current export default Map! We have made it. Refresh your application and request some places, you will see something beautiful like this:. You may have guessed again. There are 4 places where we will have to add further logic to make sure we can compute clusters with DBScan.
The actions, the reducers, the Map and of course the Controls. Let's start enhancing our reducer to make sure it can cope with a little more state. DBScans main settings consist of a minimum points and b maximum distance, if you are interested to learn how these work please check the links we provided above.
Hence, we will add some basic initial state settings to the file and extend our switch clause in our reducer. We want to both update our settings and also be able to compute the clusters and will need some actions which yet don't exist. The actions in our reducer are imported from our actions file, eureka, so go add them tiger.
It couldn't really get any simpler:. Last but not least we want to add this logic to the user interface, both controls and map. We have defined our actions and reducers which we can now connect to the controls component. And we need some simple controls, usually sliders look quite nice. Let's also add the Header and Divider class from semantic UI. Furthermore you will have to import the newly added actions.
We have 2 different actions which are dispatched in this class now, namely handleClickDbscan and updateDbScanSettings. If you drag the sliders and change the values you will, in your redux state, notice that these are updated on the fly.
Good for data which contains clusters of similar density. Read more in the User Guide. The maximum distance between two samples for one to be considered as in the neighborhood of the other. This is not a maximum bound on the distances of points within a cluster. The number of samples or total weight in a neighborhood for a point to be considered as a core point. This includes the point itself. The metric to use when calculating distance between instances in a feature array. If metric is a string or callable, it must be one of the options allowed by sklearn.
New in version 0. The algorithm to be used by the NearestNeighbors module to compute pointwise distances and find nearest neighbors. See NearestNeighbors module documentation for details. This can affect the speed of the construction and query, as well as the memory required to store the tree.
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