For a project, I have learnt to import KEGG pathways to Cytoscape and merge without any edits. I want to differentiate the nodes of each pathways with different colours to understand the pathways of particular gene or molecule. When I try to merge the pathways after editing, only the source is getting merged not the edited one. Could someone please guide me with the tips to merging the edited pathways in Cytoscape in detail?
I assume that when you say "editing" you are referring to editing the visual properties (i.e. color). You are correct that merging networks does not attempt to merge the visual properties. On the other hand, this isn't really hard -- just add a node column in one of your pathways and fill that column with a values (doesn't matter what value). When you do the merge, that column will be preserved. Now since only one of your pathways has values in the that column, you can set up a discrete mapping and change the color of only those nodes with a value in the column. This is covered in the Basic Data Visualization tutorial at https://tutorials.cytoscape.org.
Related
I am completely new to NEO4j and using it for the first time ever now for my masters program. Ive read the documentation and watched tutorials online but can’t seem to figure out how I can represent my nodes in the way I want.
I have a dataframe with 3 columns, the first represents a page name, the second also represents a page name, and the third represents a similarity score between those two pages. How can I create a graph in NEO4J where the nodes are my unique page names and the relationships between nodes are drawn if there is a similarity score between them (so if the sim-score is 0 they don’t draw a relationship)? I want to show the similarity score as the text of the relationship.
Furthermore, I want to know if there is an easy way to figure out which node had the most relationships to other nodes?
I’ve added a screenshot of the header of my DF for clarity https://imgur.com/a/pg0knh6. I hope anyone can help me, thanks in advance!
Edit: What I have tried
LOAD CSV WITH HEADERS FROM 'file:///wiki-small.csv' AS line
MERGE (p:Page {name: line.First})
MERGE (p2:Page {name: line.Second})
MERGE (p)-[r:SIMILAR]->(p2)
ON CREATE SET r.similarity = toFloat(line.Sim)
Next block to remove the similarities relationships which are 0
MATCH ()-[r:SIMILAR]->() WHERE r.Sim=0
DELETE r
This works partially. As in it gives me the correct structure of the nodes but doesn't give me the similarity scores as relationship labels. I also still need to figure out how I can find the node with the most connections.
For the first question:
How can I create a graph in NEO4J where the nodes are my unique page names and the relationships between nodes are drawn if there is a similarity score between them (so if the sim-score is 0 they don’t draw a relationship)?
I think a better approach is to remove in advance the rows with similarity = 0.0 before ingesting them into Neo4j. Could it be something feasible? If your dataset is not so big, I think it is very fast to do in Python. Otherwise the solution you provide of deleting after inserting the data is an option.
In case of a big dataset, maybe it's better if you load the data using apoc.periodic.iterate or USING PERIODIC COMMIT.
Second question
I want to know if there is an easy way to figure out which node had the most relationships to other nodes?
This is an easy query. Again, you can do it with play Cypher or using APOC library:
# Plain Cypher
MATCH (n:Page)-[r:SIMILAR]->()
RETURN n.name, count(*) as cat
ORDER BY cnt DESC
# APOC
MATCH (n:Page)
RETURN apoc.node.degree(n, "SIMILAR>") AS output;
EDIT
To display the similarity scores, in Neo4j Desktop or in the others web interfaces, you can simply: click on a SIMILARITY arrow --> on the top of the running cell the labels are shown, click on the SIMILAR label marker --> on the bottom of the running cell, at the right of Caption, select the property that you want to show (similarity in your case)
Then all the arrows are displayed with the similarity score
To the second question: I think you should keep a clear separation between the way you store data and the way you visualize it. Having the similarity score (a property of the SIMILARITY edge) as a "label" is something that is best dealt with by using an adequate viz library or platform. Ours (Graphileon) could be such a platform, although there are also others.
We offer the possibility to "style" the edges with so-called selectors like
"label":"(%).property.simScore" that would use the simScore as a label. On top of that you could do thing like
"width":"evaluate((%).properties.simScore < 0.500 ? 3 : 10)"
or
"fillColor":"evaluate((%).properties.simScore < 0.500 ? grey : red)"
to distinguish visually high simScores.
Full disclosure : I work for Graphileon.
I have 8 different datasets with the same structure. I am using Neo4j and need to query all of them at different points on the website I am developing. What would be the approaches at storing the datasets in one database?
One idea that comes to my mind is to supply for each node an additional property that would distinguish nodes of one dataset from nodes of the other ones. But that seems too repetitive and wrong for me. The other idea is just to create 8 databases and query them separately but how could I do that? Running each one in its own port seems crazy.
Any suggestions would be greatly appreciated.
If your datasets are in a tree structure, you could add a different root node to each of them that you could use for reference, similar to GraphAware TimeTree. Another option (better than a property, I think) would be to differentiate each dataset by adding a specific label to nodes from that dataset (i.e. all nodes from "dataset A" get a :DataSetA label)
I imagine that the specific structure of your dataset may yield other options. For example, if you always begin traversals of the dataset from a few set locations, you only need to be able to determine which dataset the entry points are a part of, because once entered, all traversals would be made within the same dataset <-- if that makes sense.
(I am new to Neo4J and very excited about it)
Here is my conceptual question:
Suppose we want to represent life on earth (based on a biological taxonomy hierarchy).
However, suppose at the leaves of the taxonomy tree we want to actually identify individual organisms. For example, at the mammalia branch, the homo-sapient sub-branch we want to identify each and every one of 7 billion humans and do the same for some other branches (give an ID to every living known great Ape left in the wild and so on)
Is this type of organization done with dense nodes (in the billions) ? or is it done with extensive use of labels (do labels support nesting)?
From my point of view it's better to use multiple nodes instead of multiple labels.
But it depends on the use case and what you want to do with it.
Neo4j doesn't support nested labels or some labels hierarchy.
Here are some resources which could be interesting for you
Graph Databases in Life Sciences: Bringing Biology Back to Its Nature
Open Tree of Life and Neo4j
I want to change the color of my nodes based on their properties:
Say I have many "Person" nodes. And I want those who live in New York to be red and those who live in Los Angeles to be blue. How would I write that. In cypher or in py2neo?
The styling of nodes and relationships in Neo4j Browser is controlled by a graph style sheet (GRASS), a cousin of CSS. You can view the current style by typing :style in the browser. To edit it, you can click on nodes and relationships and pick colors and sizes, or you can view the style sheet (:style), download it, make changes, and drag-n-drop it back into the view window.
Unfortunately for your case, color can only be controlled a) for all nodes and all relationships or b) for nodes by label and relationships by type. Properties can only be used for the text displayed on the node/rel.
It is not possible to interact with neo4j browser pro-grammatically. But the end goal could be achieved through a hack.
Even though I am a bit late here want to help others who might be finding a way. It is not possible to change the color of the nodes based on the property but there is a way it can be achieved by creating nodes based on the property. Keep in mind that after applying these queries your data wont be the same. So it is always a good idea to keep a backup of your data.
This is how labels are colored by default (Before):
Color based on the property
Suppose there is a label called Case with a property nationality and you want to color the nodes based on nationality. So following query could be used to create labels out of nationality property. For this you will need to install apoc library. check here for installation.
// BY NATIONALITY
MATCH (n:Case)
WITH DISTINCT n.nationality AS nationality, collect(DISTINCT n) AS persons
CALL apoc.create.addLabels(persons, [apoc.text.upperCamelCase(nationality)]) YIELD node
RETURN *
This will return all the people by nationality. Now you can color by country of nationality. Below shows an example.
Color based on the property and load with other labels
Lets say you also have a label called Cluster.The cases are attached to clusters via relationships. Just change the query to following to get the clusters with their relationships to cases.
//BY NATIONALITY WITH CLUSTERS
MATCH (n:Case),(c:Cluster)
WITH DISTINCT n.nationality AS nationality,
collect(DISTINCT n) AS persons,
collect(DISTINCT c) AS clusters
CALL apoc.create.addLabels(persons, [apoc.text.upperCamelCase(nationality)]) YIELD node
RETURN *
It will return cases and clusters with all the relationships. Below shows example.
Please leave an up vote if this was helpful and want to let others know that this is an acceptable answer. Thank you.
You cannot include formatting of the output in Cypher queries in the neo4j browser. Currently, the only way is to change the graph view manually or load a graph style file.
See tutorial here: http://neo4j.com/developer/guide-neo4j-browser/
Also, you cannot interact with the neo4j browser from py2neo.
If you are happy setting the color through a graphical user interface rather than programatically, Neo4j also supplies a data exploration addon named bloom. When using this addon (now automatically installed when using neo4j desktop), it is possible to set node color based on its properties.
In the example below, movies released after 2002 are colored green.
We are working on a system where users can define their own nodes and connections, and can query them with arbitrary queries. A user can create a "branch" much like in SCM systems and later can merge back changes into the main graph.
Is it possible to create an efficient data model for that in Neo4j? What would be the best approach? Of course we don't want to duplicate all the graph data for every branch as we have several million nodes in the DB.
I have read Ian Robinson's excellent article on Time-Based Versioned Graphs and Tom Zeppenfeldt's alternative approach with Network versioning using relationnodes but unfortunately they are solving a different problem.
I Would love to know what you guys think, any thoughts appreciated.
I'm not sure what your experience level is. Any insight into that would be helpful.
It would be my guess that this system would rely heavily on tags on the nodes. maybe come up with 5-20 node types that are very broad, including the names and a few key properties. Then you could allow the users to select from those base categories and create their own spin-offs by adding tags.
Say you had your basic categories of (:Thing{Name:"",Place:""}) and (:Object{Category:"",Count:4})
Your users would have a drop-down or something with "Thing" and "Object". They'd select "Thing" for instance, and type a new label (Say "Cool"), values for "Name" and "Place", and add any custom properties (IsAwesome:True).
So now you've got a new node (:Thing:Cool{Name:"Rock",Place:"Here",IsAwesome:True}) Which allows you to query by broad categories or a users created categories. Hopefully this would keep each broad category to a proportional fraction of your overall node count.
Not sure if this is exactly what you're asking for. Good luck!
Hmm. While this isn't insane, think about the type of system you're replacing first. SQL. In SQL databases you wouldn't use branches because it's data storage. If you're trying to get data from multiple sources into one DB, I'd suggest exporting them all to CSV files and using a MERGE statement in cypher to bring them all into your DB at once.
This could manifest similar to branching by having each person run a script on their own copy of the DB when you merge that takes all the nodes and edges in their copy and puts them all into a CSV. IE
MATCH (n)-[:e]-(n2)
RETURN n,e,n2
Then comparing these CSV's as you pull them into your final DB to see what's already there from the other copies.
IMPORT CSV WITH HEADERS FROM "file:\\YourFile.CSV" AS file
MERGE (N:Node{Property1:file.Property1, Property2:file.Property2})
MERGE (N2:Node{Property1:file.Property1, Property2:file.Property2})
MERGE (N)-[E:Edge]-(N2)
This will work, as long as you're using node types that you already know about and each person isn't creating new data structures that you don't know about until the merge.