==============================================================================
README: CYTOSCAPE

         file: /mnt/Vancouver/programming/cytoscape/_readme-cytoscape-victoria.txt
last modified: 2019-08-13
==============================================================================

[victoria@victoria cytoscape]$ dpl

  Fri 02 Aug 2019 01:50:07 PM PDT
  /mnt/Vancouver/apps/cytoscape
  total 16
  drwxr-xr-x 6 victoria victoria 4096 Jul 15 09:44 cytoscape-3.7.1
  drwxr-xr-x 2 victoria victoria 4096 Aug  2 13:41 kegg
  drwxr-xr-x 2 victoria victoria 4096 May 27 20:28 src
  drwxr-xr-x 3 victoria victoria 4096 May 28 14:02 web

[victoria@victoria cytoscape]$ yay -Ss cytoscape
  aur/cytoscape 3.7.1-1 (+11 0.36%)
    A software for visualizing molecular interaction networks and integration with gene expression profiles and other state data.

==============================================================================

* GitHub: https://github.com/cytoscape
* manual: http://manual.cytoscape.org/en/stable/index.html
* Google group: https://groups.google.com/forum/#!forum/cytoscape-helpdesk

*    tutorials: https://github.com/miriamposner/cytoscape_tutorials

 ** Command Line Arguments: http://manual.cytoscape.org/en/stable/Command_Line_Arguments.html#command-line-arguments
 ** Node and Edge Column Data: http://manual.cytoscape.org/en/stable/Node_and_Edge_Column_Data.html#node-and-edge-column-data

* https://cytoscape.org/manual/Cytoscape3_6_0Manual.pdf

Lines in the SIF file specify a source node, a relationship type (or edge type), and one or more target nodes:

  nodeA <relationship type> nodeB
  nodeC <relationship type> nodeA
  nodeD <relationship type> nodeE nodeF nodeB
  nodeG
  ...
  nodeY <relationship type> nodeZ

A more specific example is:

  node1 typeA node2
  node2 typeB node3 node4 node5
  node0

The first line identifies two nodes, called node1 and node2, and a single relationship between node1 and node2 of typetypeA. The second line specifies three new nodes, node3, node4, and node5; here “node2” refers to the same node asin the first line. The second line also specifies three relationships, all of type typeB and with node2 as the source, withnode3, node4, and node5 as the targets. This second form is simply shorthand for specifying multiple relationships ofthe same type with the same source node. The third line indicates how to specify a node that has no relationships withother nodes.  This form is not needed for nodes that do have relationships, since the specification of the relationshipimplicitly identifies the nodes as well.

Duplicate entries are ignored.  Multiple edges between the same nodes must have different edge types.  For example,the following specifies two edges between the same pair of nodes, one of type xx and one of type yy:

  node1 xx node2
  node1 xx node2
  node1 yy node2

Edges connecting a node to itself (self-edges) are also allowed:

  node1 xx node1

Every node and edge in Cytoscape has a name column.  For a network defined in SIF format, node names should beunique, as identically named nodes will be treated as identical nodes. The name of each node will be the name in this file by default (unless another string is mapped to display on the node using styles). This is discussed in the section onStyles. The name of each edge will be formed from the name of the source and target nodes plus the interaction type:for example, sourceName (edgeType) targetName.

The tag can be any string.  Whole words or concatenated words may be used to define types of relationships, e.g. geneFusion, cogInference, pullsDown, activates, degrades, inactivates, inhibits, phosphorylates, upRegulates, etc.

Some common interaction types used in the Systems Biology community are as follows:

  pp : protein - protein interaction
  pd : protein -> DNA (e.g. transcription factor binding upstream of a regulating gene.)

Some less common interaction types used are:

  pr : protein -> reaction
  rc : reaction -> compound
  cr : compound -> reaction
  gl : genetic lethal relationship
  pm : protein-metabolite interactiob
  mp : metabolite-protein interaction
  ...

------------------------------------------------------------------------------
* UTILITIES:
------------

 **        py2cytoscape : Python utilities for Cytoscape and Cytoscape.js

 ** Cytoscape automation: collection of scripts that include programmatic I/O and control of Cytoscape

  *** https://github.com/cytoscape/cytoscape-automation
      https://github.com/cytoscape/cytoscape-automation/wiki                    ## << this!

  *** https://github.com/cytoscape/cytoscape-automation/wiki#python-notebooks

 **   cyREST | cyclient : Cytoscape 3 access for external tools via a language agnostic RESTful API

 **           KEGGlincs : visualize all edges within a KEGG pathway and overlay LINCS data
 **             cyto_vis: send graph to Cytoscape via CyREST utility functions, to view the KEGG pathway in Cytoscape
 **           KEGGscape : Cytoscape app for importing KGML (KEGG pathway XML)

==============================================================================
APPS
====

* Can install these within Cytoscape (Apps menu) or from Apps webpage (if Cytoscape instance running):

 ** explanation

----------------------------------------
* enhancedGraphics : passthrough mapper for charts and gradients (add charts to nodes;
    https://apps.cytoscape.org/apps/enhancedgraphics

 ** e.g.: file:///mnt/Vancouver/domains/PERSAGEN.com/2.0/files/misc/cytoscape-metabolome-profile.png
 ** e.g.: https://cytoscape.org/cytoscape-automation/for-scripters/R/notebooks/Custom-Graphics.nb.html#enhanced_graphics

----------------------------------------
* KEGGscape : file reader and pathway visualizer for KEGG XML (KGML) files
  https://apps.cytoscape.org/apps/keggscape

 ** You can import KEGG pathway [directly into!] Cytoscape by requesting the pathway ID.  For example you can import

    http://www.genome.jp/dbget-bin/www_bget?eco00010

   by requesting

    http://localhost:1234/keggscape/v1/eco00010

----------------------------------------

* ReactomeFIPlugIn
  https://apps.cytoscape.org/apps/reactomefiplugin

  Explore Reactome pathways and search for diseases related pathways and network patterns using the Reactome functional interaction network. ...

  ReactomeFIViz (also called Reactome Cytoscape Plugin or ReactomeFIPlugIn) is designed to find pathways and network patterns related to cancer and other types of diseases. This plugin accesses the Reactome pathways stored in the database, help you to do pathway enrichment analysis for a set of genes, visualize hit pathways using manually laid-out pathway diagrams directly in Cytoscape, and investigate functional relationships among genes in hit pathways.

  The plugin can also access the Reactome Functional Interaction (FI) network, a highly reliable, manually curated pathway-based protein functional interaction network covering over 50% of human proteins, and allows you to construct a FI sub-network based on a set of genes, query the FI data source for the underlying evidence for the interaction, build and analyze network modules of highly-interacting groups of genes, perform functional enrichment analysis to annotate the modules, expand the network by finding genes related to the experimental data set, display pathway diagrams, and overlay with a variety of information sources such as cancer gene index annotations.


----------------------------------------

* ReNE: Regulatory Network Enhancing Plugin
  https://apps.cytoscape.org/apps/rene

 ** ReNE allows users to enhance standard KEGG/Reactome pathways with information regarding: Transcription Factors, Proteins and MicroRNAs. Such enhancement allows to better understand/inspect possible regulatory motifs which involve entities commonly not presented into pathways. ...


==============================================================================
CYTOSCAPE.JS
============

* Cytoscape.js: http://js.cytoscape.org/#introduction                           ## replaces Cytoscape Web [deprecated: http://cytoscapeweb.cytoscape.org/]

* py2cytoscape
  https://py2cytoscape.readthedocs.io/en/latest/

    py2cytoscape is a collection of utilities to use Cytoscape and Cytoscape.js from Python. Network visualization feature is still limited in Python, but with this tool, you can access both of Cytoscape and Cytoscape.js as network visualization engines for your Python code!

  Data Conversion Utilities to/from Cytoscape.js JSON
  https://github.com/cytoscape/cytoscape-automation/tree/master/for-scripters

* Loading JSON file into Cytoscape.js 
  https://stackoverflow.com/a/41646474/1904943
  
  Cytoscape desktop erroneously names the exported file with the extension .cyjs. It's just a JSON file, so rename it to .json. Just point Cytoscape.js to the particular parts of the JSON you want to use (when you call cytoscape( myOptions ).

* [2014] How to export all graph data including [node] position info from Cytoscape.js graph?

    Load your network into Cytoscape 3.1.1 (or 3.2.0 nightly build)
    Apply layout, move nodes, edit styles, etc.
    Select File-->Export --> Network and View...
    Select .cyjs format and name your file
    Press OK.

    This generates a Cytoscape.js-readable JSON file including (x,y) position of nodes.  Optionally, you can export Visual Styles into a JSON file and use it with the network JSON.

    By the way, if you need to export multiple network JSON files at once, you can use Cytoscape 3.2.0 nightly build and use "Export as Interactive Web Visualization" option.  This generates web application from your networks.  And in data folder, it has all of your networks in Cytoscape.js-style JSON.

      http://wiki.cytoscape.org/Cytoscape_3/UserManual/Publish

    OR, you can use cyREST:

      http://apps.cytoscape.org/apps/cyrest

    Install it from the App store and access the following URL using node.js, python, R, curl, web browser, etc.

      http://localhost:1234/v1/networks.json

    This generates array of your networks in Cytoscape.js compatible JSON.  Note that both options require Java 7.

    ----------------------------------------
    Thanks Kei for your reply, but my question is how to export data from graph in my web graph which was made via cytoscape js library (not cytoscape software). I want to export all node, edge data and their position in the graph.

    ----------------------------------------
    That's simpler:

      http://js.cytoscape.org/#core/export/cy.json

    And this JSON can be used in BOTH cytoscape.js and Cytoscape desktop. 

* Introduction to py2cytoscape: Pythonista-friendly wrapper for cyREST
  https://nbviewer.jupyter.org/github/idekerlab/py2cytoscape/blob/develop/examples/New_wrapper_api_sample.ipynb
  https://github.com/cytoscape/py2cytoscape/blob/develop/examples/New_wrapper_api_sampl    ## << this displays better

* Using Cytoscape.js in Jupyter Notebook
  https://github.com/idekerlab/cy-rest-python/blob/f789203044b4dc870a8b63572a935f92fbd9b89d/basic/CytoscapeJS_visualization.ipynb

----------------------------------------
DATA CONVERSION UTILITIES FROM/TO Cytoscape.js JSON:

http://js.cytoscape.org/

Cytoscape.js JSON is one of the standard data exchange formats in Cytoscape community. py2cytoscape includes some graph data conversion utilities for popular graph analysis packages in Python.

Currently, the following graph objects are supported:

  NetworkX - From / To Cytoscape.js JSON
    igraph - From / To Cytoscape.js JSON
      pandas DataFrame - To Cytoscape.js JSON

------------------------------------------------------------------------------
DEMOS:

* Cytoscape.js tutorial demo
  https://cytoscape.org/cytoscape.js-tutorial-demo/
  https://github.com/cytoscape/cytoscape.js-tutorial-demo
  https://raw.githubusercontent.com/cytoscape/cytoscape.js-tutorial-demo/gh-pages/index.html
 ** includes genes data: https://github.com/cytoscape/cytoscape.js-tutorial-demo/blob/gh-pages/datasets/genes.json

* Cola.js/Cytoscape.js demo graph of gene-gene interactions; uses Cola.js for layout & Cytoscape.js for graph model & visualisation
  https://js.cytoscape.org/demos/colajs-graph/

 ** http://genemania.org/
    http://genemania.org/search/homo-sapiens/brca1/fen1                         ## pretty neat; based on:
 ** http://apps.cytoscape.org/apps/genemania

* d3.js:
 ** cytoscape-d3 : Cytoscape to D3.js Exporter, a Cytoscape app for exporting network and data table to D3.js style JSON
    https://github.com/keiono/
    https://github.com/keiono/cytoscape-d3
    http://chianti.ucsd.edu/~kono/cy3js/d3-tree.html

* Cytoscape.js Layout Demo
  http://www.cs.bilkent.edu.tr/~ivis/Cytoscape_LayoutDemo/#

* CerebralWeb javascript layout plugin for Cytoscape.js
  https://www.innatedb.ca/CerebralWeb/
  https://www.innatedb.ca/CerebralWeb/demos.php

  Provided by InnateDB.ca, a publicly available database of the genes, proteins, experimentally-verified interactions     ## SFU | UBC! https://www.innatedb.ca/redirect.do?go=aboutIDB
  and signaling pathways involved in the innate immune response of humans, mice and bovines to microbial infection.

* dash-cytoscape
  https://github.com/plotly/dash-cytoscape

  https://xinghanlu.com/projects/
  Dash Cytoscape is a graph visualization component for creating easily customizable, high-performance, interactive, and web-based networks. It extends and renders Cytoscape.js, and offers deep integration with Dash layouts and callbacks, enabling the creation of powerful networks in conjunction with the rich collection of Dash components, as well as established computational biology and network science libraries such as BioPython and NetworkX.

* http://www.wineandcheesemap.com/

------------------------------------------------------------------------------
JAVASCRIPT

* "onchange" event listener example (calls function)
  https://www.w3schools.com/jsref/tryit.asp?filename=tryjsref_onchange_html

  "onclick" event listener --- buttons, text input fields ...
  http://embed.plnkr.co/O7mWEfZuIhhtahdAhsAM/

* cytoscape js selector demo
  https://codepen.io/yeoupooh/pen/BjWvRa

* JS selectors [slide 16: https://co.mbine.org/events/COMBINE_2012/agenda?q=system/files/2012-08-17-combine-bader-franz-cytoscape.pdf]
  cy.$('node[weight > 50]{degree > 2}')                                         ## [ ] for client-defined data; { } for metadata

  https://raw.githubusercontent.com/kzuberi/ipython-cytoscape.js/master/examples/no_widget.ipynb


==============================================================================
ATTRIBUTES | LABELS | PROPERTIES
================================

* [2019-08-08] /mnt/Vancouver/programming/data/metabolism/practice/cytoscape/

  I was only able to add one edge attribute, via the edge visual style "Tooltip" tool.  The GitHub repo, below, apparently addresses this issue.

* How to add html label to cytoscape graph node                                 ## I believe this is how to add a URL to a node ...
  https://stackoverflow.com/questions/45658912/how-to-add-html-label-to-cytoscape-graph-node

 ** cytoscape-node-html-label
    https://github.com/kaluginserg/cytoscape-node-html-label

 ** Display more attributes per node/edge
    https://groups.google.com/forum/#!searchin/cytoscape-helpdesk/multiple$20attributes%7Csort:date/cytoscape-helpdesk/x4b76auy9SY/OIrEUeSJBAAJ

    How to add set label from different fields
    https://groups.google.com/forum/#!searchin/cytoscape-helpdesk/multiple$20columns%7Csort:date/cytoscape-helpdesk/4yfvZ5IGVq8/DXuFk_WuEAAJ

 ** How to Prepare Data for Import into Cytoscape (Version 3.2.1, released February 2015)
    https://ebeshero.github.io/thalaba/cytosc.html#dataImport

      "...
      In Cytoscape, information that describes qualities of particular nodes or edges is known as attribute data, and we can have node attributes and edge attributes.

      Your first import to Cytoscape will only submit the node, edge, and node columns, plus a column identified as "edge attributes."

      You may import, in a second stage, the attribute information about your nodes. We can write XSLT or XQuery to output text arrayed in columns with a separator, knowing that we can import data in tab-separated or comma-separated columns.

      I prepare a single text file containing all of my node data, node attribute data, edge data, edge attribute data, and connected node data and connected attribute data, and I use that file twice: once to initiate the network, and again to add node attribute data.
      ..."

 ** Node and Edge Column Data
    http://manual.cytoscape.org/en/stable/Node_and_Edge_Column_Data.html#node-and-edge-column-data

    Legacy Cytoscape Attributes Format
    http://manual.cytoscape.org/en/stable/Node_and_Edge_Column_Data.html#legacy-cytoscape-attributes-format

 ** Working with Attributes
    https://github.com/miriamposner/cytoscape_tutorials/blob/master/working-with-attributes.md


==============================================================================
NETWORKS!!!  :-O
================

* NDEx: https://www.ndexbio.org/#/                                            ## ability -- apparently -- to DIRECTLY import those to Cytoscape!!

 ** NDEx is an academic project, not-for-profit, open source and 100% FREE!
 ** https://www.ndexbio.org/#/search?searchType=All&searchString=genes&searchTermExpansion

    file:///mnt/Vancouver/projects/files/cytoscape_NDEx.png

    Mutations in Melanoma Genes
    Drugs Targeting Melanoma Genes
    Pathways Affected by Melanoma Genes
    CTD: Genes-Pathways Associations
    Drugs Targeting Melanoma Genes
    Pathways Affected by Melanoma Genes
    CTD: Chemicals-Genes Interactions
    ... ... ...

  ** NOTE: Firefox wouldn't let me open those in Cytoscape or even d/l them, but Opera did!!

  ** [R] Cytoscape and NDEx
     https://cytoscape.org/cytoscape-automation/for-scripters/R/notebooks/Cytoscape-and-NDEx.nb.html

------------------------------------------------------------------------------
REACTOME DATABASE:
--------------------

* https://reactome.org/

* schema: https://reactome.org/content/schema/DatabaseObject

* Cytoscape Reactome FI Example: https://github.com/reactome-fi/workflows/blob/master/CytoscapeReactomeFI.ipynb
    This example demonstrates a workflow using ReactomeFIViz CyREST API to perform a comparison pathway and network analysis for TCGA BRCA (breast invasive carcinoma) and OV (ovarian serous cystadenocarcinoma) mutation data.

 ** FIViz: Functional Interaction Vizualization: https://reactome.org/tools/reactome-fiviz

    The ReactomeFIViz app is designed to find pathways and network patterns related to cancer and other types of diseases. This app accesses the Reactome pathways stored in the database, help you to do pathway enrichment analysis for a set of genes, visualize hit pathways using manually laid-out pathway diagrams directly in Cytoscape, and investigate functional relationships among genes in hit pathways. ...

 ** https://reactome.org/tools/reactome-fiviz#Download_and_Launch_ReactomeFIViz

    ReactomeFIViz app 6 needs Cytoscape 3.7.0 or above. If you have not installed Cytoscape 3.7.0 or above, please download it from Cytoscape's web site: http://www.cytoscape.org. After launching Cytoscape, use menu "Apps/App Manager" to open the "App Manager" dialog, and search for "ReactomeFI". You should see the ReactomeFIViz app listed in the middle panel (See the Figure below. You may see a different version number. Note: The listed name of this app is "ReactomeFIPlugIn", which is the original name of the app.). Choose the app, and then click the "Install" button at the bottom of the dialog. Follow the procedures to finish the installation.  ...




==============================================================================
KEGG
====

* NOTE re: KGML files -- (Glycolysis / Gluconeogenesis) available here          ## genome.jp

  https://www.genome.jp/kegg-bin/show_pathway?hsa00010

    [ Pathway menu | Organism menu | Pathway entry | ***DOWNLOAD KGML***  | Show description | User data mapping ]

not here                                                                        ## kegg.jp

  https://www.kegg.jp/kegg-bin/show_pathway?org_name=hsadd&mapno=00010&mapscale=&show_description=show

    [ Pathway menu | Hide description | Disease/drug list | User data mapping ]

------------------------------------------------------------------------------
2019-08-02

Downloaded Glycolysis/Gluconeogenesis - Homo sapiens (human) KGML file

  https://www.kegg.jp/kegg-bin/download?entry=hsa00010&format=kgml

to

  /mnt/Vancouver/apps/cytoscape/kegg/hsa00010-glycolysis.kgml

Cytoscape >> File menu >> Import >> Network from file >> [select above .kgml XML file] >> Create new network collection | check: Import pathway details from KEGG database >> OK

  file:///mnt/Vancouver/projects/files/cytoscape-glycolysis_kgml_import-2019.08.02a.png

Imports that pathway into Cytoscape!!  :-D

Saved as Cytoscape session

  /mnt/Vancouver/apps/cytoscape/sessions/kegg-hsa00010-glycolysis-human.cys

  file:///mnt/Vancouver/projects/files/cytoscape-glycolysis_kgml_import-2019.08.02b.png


==============================================================================
py2cytoscape
============

GitHub: https://github.com/cytoscape/py2cytoscape                               ## Python utilities for Cytoscape and Cytoscape.js
 intro: https://github.com/cytoscape/cytoscape-automation/tree/master/for-scripters/Python
        https://github.com/cytoscape/cytoscape-automation/blob/master/for-scripters/Python/basic-fundamentals.ipynb
  docs: https://py2cytoscape.readthedocs.io/en/latest/
  demo: https://github.com/cytoscape/cytoscape-automation/blob/master/for-scripters/Python/basic-feature-demos.ipynb
        https://github.com/cytoscape/cytoscape-automation/blob/master/for-scripters/Python/advanced-cancer-networks-and-data.ipynb                              ## + cytoscape-automation

        Introduction to py2cytoscape: Pythonista-friendly wrapper for cyREST
        https://nbviewer.jupyter.org/github/idekerlab/py2cytoscape/blob/develop/examples/New_wrapper_api_sample.ipynb
        https://github.com/cytoscape/py2cytoscape/blob/develop/examples/New_wrapper_api_sample.ipynb    ## << this displays better

        CyREST: Turbocharging Cytoscape Access for External Tools via a RESTful API [2015]
        https://f1000research.com/articles/4-478/v1

------------------------------------------------------------------------------
Cytoscape automation:

  https://github.com/cytoscape/cytoscape-automation                             ## Collection of scripts that include programmatic I/O and control of Cytoscape

  https://github.com/cytoscape/cytoscape-automation/wiki

    Resources are organized into categories below, leveraging R and Python libraries:

      * RCy3 package

      * py2cytoscape utility

      * Python Notebooks (https://github.com/cytoscape/cytoscape-automation/wiki#python-notebooks) -- includes

        ** Network Assisted Genomic Analysis (NAGA): https://github.com/shfong/naga/blob/master/notebooks/tutorial.ipynb
           Re-prioritizes significant single nucleotide polymorphisms (SNPs) to genes using network diffusion methods including random walk and heat diffusion.

        ** Cytoscape Reactome FI Example: https://github.com/reactome-fi/workflows/blob/master/CytoscapeReactomeFI.ipynb
           This example demonstrates a workflow using ReactomeFIViz CyREST API to perform a comparison pathway and network analysis for TCGA BRCA (breast invasive carcinoma) and OV (ovarian serous cystadenocarcinoma) mutation data

  https://github.com/cytoscape/cytoscape-automation/blob/master/for-scripters/Python/advanced-cancer-networks-and-data.ipynb    ## << fabulous demo!!!
  https://docs.google.com/document/d/1QTrT-9ylhI4OX5DkauMo2ujLIqeg3WDUDwl77KLtfVY/edit

https://f1000research.com/articles/7-822/v2
Copycat Layout: Network layout alignment via Cytoscape Automation

  The copycatLayout app is a network-based visual differential analysis tool that improves upon the existing layoutSaver app and is delivered pre-installed with Cytoscape, beginning with v3.6.0. LayoutSaver cloned a network layout by mapping node locations from one network to another based on node attribute values, but failed to clone view scale and location, and provided no means of identifying which nodes were successfully mapped between networks. Copycat addresses these issues and provides additional layout options.

  With the advent of Cytoscape Automation (packaged in Cytoscape v3.6.0), researchers can utilize the Copycat layout and its output in workflows written in their language of choice by using only a few simple REST calls. Copycat enables researchers to visually compare groups of homologous genes,generate network comparison images for publications, and quickly identify differences between similar networks at a glance without leaving their script.

  With a few extra REST calls, scripts can discover nodes present in one network but not in the other, which can feed into more complex analyses (e.g.,modifying mismatched nodes based on new data, then re-running the layout to highlight additional network changes).


========================================
py2cytoscape INSTALLATION
=========================

Latest stable release:

  pip3 install py2cytoscape

Development version:

  pip3 install git+https://github.com/cytoscape/py2cytoscape.git

https://github.com/cytoscape/py2cytoscape/issues/81
https://github.com/cytoscape/py2cytoscape#installation

http://localhost:1234/v1/

------------------------------------------------------------------------------

py2cytoscape is a collection of utilities to use Cytoscape and Cytoscape.js from Python. ...  We want to introduce cy2cytoscape [typo: they mean py2cytoscape!], along with cyREST and Jupyter Notebook ...

py2cytoscape depends on python-igraph and optionally depends on scipy.

...
cyREST is a language-agnostic RESTful API for Cytoscape 3. Of course you can drive Cytoscape by calling raw RESTful API using requests or other http client library, but with this wrapper, you can significantly reduce your lines of code:

  from py2cytoscape.data.cyrest_client import CyRestClient

  cy = CyRestClient()
  network = cy.network.create(name='My Network', collection='My network collection')
  print(network.get_id())

----------------------------------------
https://stackoverflow.com/questions/54411663/py2cytoscape-automate-saving-view

[Mar 2019]  There have been small changes with Cytoscape 3.7.1.  Please install py2cytoscape from the development branch

  pip uninstall py2cytoscape
  pip install git+https://github.com/cytoscape/py2cytoscape.git --user          ## Victoria: don't need "--user"

and then use

    cytoscape.view.export(options="PDF", outputFile="FILENAME")


========================================
cyREST | cyclient
=================

Cytoscape Access for External Tools via a RESTful API

GitHub: https://github.com/idekerlab/cy-rest-python                             ## cyREST examples for Python users
 intro: https://nbviewer.jupyter.org/github/idekerlab/py2cytoscape/blob/develop/examples/New_wrapper_api_sample.ipynb
 demos: https://github.com/idekerlab/cy-rest-python/blob/develop/index.ipynb
        https://nbviewer.jupyter.org/github/idekerlab/cy-rest-python/blob/develop/advanced/CytoscapeREST_KEGG_time_series.ipynb

        Welcome to cyREST Examples for Python Users!
        https://nbviewer.jupyter.org/github/idekerlab/cy-rest-python/blob/develop/index.ipynb

A CyREST client:

cyclient(host="localhost", port=1234, version="V1")

  host CyREST host server address. default='localhost'
  port CyREST port number. default=1234
  version CyREST version. default='v1'
  returns status a cyclient object.

cyclient.status()     ## checks the status of your CyREST server.
cyclient.version()    ## checks Cytoscape version.
cyclient.copy()       ## creates a copy of the cyclient object.

[ ... SNIP! ... ]

>>> from py2cytoscape import cyrest
>>> ## cytoscape=cyrest.cyclient()
>>> cy=cyrest.cyclient()
>>> cy
  <py2cytoscape.cyrest.cyrest.cyclient object at 0x7fefd66b0358>
>>> cy.status()
  CyREST online!
>>> cy.version()
  apiVersion v1
  cytoscapeVersion 3.7.1
>>> cy2=cy.copy()
>>> cy2
  <py2cytoscape.cyrest.cyrest.cyclient object at 0x7feff0ee9cc0>


==============================================================================
py2cytoscape SESSION [2019-07-06]
=================================

[Python 3.7 (py37 | p37) venv:]

(py37) [victoria@victoria networkx]$ d
  Fri 05 Jul 2019 11:46:55 AM PDT

(py37) [victoria@victoria networkx]$ python --version
  Python 3.7.3

## pip IS pip3

(py37) [victoria@victoria networkx]$ pip install git+https://github.com/cytoscape/py2cytoscape.git

  Collecting git+https://github.com/cytoscape/py2cytoscape.git
  [ ... snip ... ]
  Successfully built py2cytoscape pydotplus
  Installing collected packages: pydot, pydotplus, py2cytoscape
  Successfully installed py2cytoscape-0.7.1 pydot-1.4.1 pydotplus-2.0.2

(py37) [victoria@victoria networkx]$ P
  Python 3.7.3 (default, Jun 24 2019, 04:54:02)
  [GCC 9.1.0] on linux
  Type "help", "copyright", "credits" or "license" for more information.

>>> import scipy
>>> import numpy

>>> import py2cytoscape

## https://py2cytoscape.readthedocs.io/en/latest/

>>> from py2cytoscape.data.cyrest_client import CyRestClient

>>> cy = CyRestClient()
  Traceback (most recent call last):
    [ ... snip ... ]
    requests.exceptions.ConnectionError: HTTPConnectionPool(host='localhost', port=1234): Max retries exceeded with url: /v1/styles/visualproperties (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7fefc1964588>: Failed to establish a new connection: [Errno 111] Connection refused'))

## SOLUTION: start Cytoscape desktop client!

>>> cy = CyRestClient()

>>> cy.version()
  Traceback (most recent call last):
    File "<console>", line 1, in <module>

>>> from py2cytoscape import cyrest                                             ## https://github.com/cytoscape/cytoscape-automation/blob/master/for-scripters/Python/advanced-cancer-networks-and-data.ipynb
>>> cytoscape=cyrest.cyclient()
>>> cytoscape.version()
  apiVersion v1
  cytoscapeVersion 3.7.1

## In Cytoscape >> Apps >> ... install StringApp

>>> from py2cytoscape.cyrest.base import api

## Takes ~5 sec; auto opens in Cytoscape:                                       ## file:///mnt/Vancouver/projects/files/cytoscape-automation-2019.07.05a.png
>>> api(namespace="string",command="disease query",PARAMS={"disease":"breast cancer","cutoff":"0.9", "species":"Homo sapiens","limit":"150"})
  {'SUID': 1184}

>>> cytoscape.network.list()
  {'networks': [1184, 52]}

>>> cytoscape.layout.circular()
>>> print(cytoscape.commands.namespace("layout"))
  Available commands for 'layout':
    apply preferred
    attribute-circle
    attributes-layout
    circular
    copycat
    cose
    degree-circle
    force-directed
    fruchterman-rheingold
    get preferred
    grid
    hierarchical
    isom
    kamada-kawai
    set preferred
    stacked-node-layout

>>> cytoscape.layout.force_directed(defaultSpringCoefficient=".000004", defaultSpringLength="5")
>>> print(cytoscape.commands.command("layout","force-directed"))
  Available arguments for 'layout force-directed':
    defaultEdgeWeight
    defaultNodeMass
    defaultSpringCoefficient
    defaultSpringLength
    edgeAttribute
    isDeterministic
    maxWeightCutoff
    minWeightCutoff
    network
    nodeAttribute
    nodeList
    numIterations
    singlePartition
    type

>>> cytoscape.node.list_attributes()
  ['SUID',
  'shared name',
  'name',
  'selected',
  'canonical name',
  'display name',
  'full name',
  'database identifier',
  'description',
  '@id',
  'namespace',
  'node type',
  'query term',
  'sequence',
  'species',
  'STRING style',
  'enhancedLabel Passthrough',
  'canonical',
  'compartment cytoskeleton',
  'compartment cytosol',
  'compartment endoplasmic reticulum',
  'compartment golgi apparatus',
  'compartment mitochondrion',
  'compartment nucleus',
  'compartment plasma membrane',
  'image',
  'target development level',
  'target family',
  'tissue adrenal gland',
  'tissue blood',
  'tissue bone',
  'tissue bone marrow',
  'tissue eye',
  'tissue gall bladder',
  'tissue heart',
  'tissue intestine',
  'tissue kidney',
  'tissue liver',
  'tissue lung',
  'tissue muscle',
  'tissue nervous system',
  'tissue pancreas',
  'tissue saliva',
  'tissue skin',
  'tissue spleen',
  'tissue stomach',
  'tissue thyroid gland',
  'tissue urine',
  'disease score']
>>> disease_score_table=cytoscape.table.getTable(columns=['disease score'],table='node')

>>> disease_score_table.head()
                      disease score
9606.ENSP00000309913       2.998750
9606.ENSP00000349016       2.998750
9606.ENSP00000221992       2.569643
9606.ENSP00000322457       3.291596
9606.ENSP00000265171       2.937734

>>> import seaborn as sns
  Traceback (most recent call last):
    File "<console>", line 1, in <module>
  ModuleNotFoundError: No module named 'seaborn'

## (needed to "pip install seaborn" in another py37 venv session)

>>> import seaborn as sns
>>> sns.set_style("white")
>>> sns.kdeplot( disease_score_table["disease score"] )
  <matplotlib.axes._subplots.AxesSubplot object at 0x7feff43a1fd0>

>>> import matplotlib
>>> import matplotlib.pyplot as plt
>>> plt.xlabel("disease score")
  Text(0.5, 0, 'disease score')
>>> plt.ylabel("frequency")
  Text(0, 0.5, 'frequency')

>>> plt.show()                                                                  ## file:///mnt/Vancouver/projects/files/cytoscape-automation-2019.07.05b.png

>>> top_quart=disease_score_table[["disease score"]].quantile(0.75)[0]
>>> top_quart
  3.64357375

>>> top_nodes=disease_score_table[disease_score_table["disease score"]>top_quart].index.tolist()
>>> top_nodes
  ['9606.ENSP00000261769',
  '9606.ENSP00000369497',
  '9606.ENSP00000405330',
  '9606.ENSP00000372023',
  '9606.ENSP00000352271',
  '9606.ENSP00000342235',
  '9606.ENSP00000369816',
  '9606.ENSP00000441765',
  '9606.ENSP00000260947',
  '9606.ENSP00000265433',
  '9606.ENSP00000295736',
  '9606.ENSP00000324856',
  '9606.ENSP00000451974',
  '9606.ENSP00000371194',
  '9606.ENSP00000261584',
  '9606.ENSP00000424328',
  '9606.ENSP00000336701',
  '9606.ENSP00000451828',
  '9606.ENSP00000325120',
  '9606.ENSP00000278616',
  '9606.ENSP00000363804',
  '9606.ENSP00000269571',
  '9606.ENSP00000259008',
  '9606.ENSP00000309572',
  '9606.ENSP00000219746',
  '9606.ENSP00000418960',
  '9606.ENSP00000351273',
  '9606.ENSP00000382423',
  '9606.ENSP00000379683',
  '9606.ENSP00000410294',
  '9606.ENSP00000263967',
  '9606.ENSP00000275493',
  '9606.H19',
  '9606.ENSP00000372088',
  '9606.ENSP00000269305',
  '9606.ENSP00000361021',
  '9606.ENSP00000303939',
  '9606.ENSP00000227507']

## [ ... SNIP! ... ] FABULOUS!!  https://github.com/cytoscape/cytoscape-automation/blob/master/for-scripters/Python/advanced-cancer-networks-and-data.ipynb



>>> [Ctrl-D]

(py37) [victoria@victoria networkx]$



==============================================================================
==============================================================================
KEGG IN {CYTOSCAPE | R}
==============================================================================
==============================================================================

https://rdrr.io/search?q=cytoscape

==============================================================================
KEGGlincs
=========

* https://rdrr.io/bioc/KEGGlincs/
  KEGGlincs: : visualize all edges within a KEGG pathway and overlay LINCS data

* https://rdrr.io/bioc/KEGGlincs/man/cyto_vis.html
  cyto_vis: Send graph to Cytoscape via CyREST

 ** View the KEGG pathway in Cytoscape. With either the 'expanded edges' or 'stacked nodes' layout, users can visualize and interact with the graphs [strictly] as they are documented in the most recent KGML available from KEGG. This function is a modified version of the function send2cy(), which is part of the cyREST utility functions.

 ** Script: https://rdrr.io/bioc/KEGGlincs/man/cyto_vis.html
    /mnt/Vancouver/programming/R/scripts/kegg_p53_signaling.R


========================================
KEGGlincs INSTALLATION [2019-07-06]
===================================

https://bioconductor.org/packages/release/bioc/html/KEGGlincs.html

  install.packages("BiocManager")                                               ## https://cran.r-project.org/web/packages/BiocManager/index.html
  BiocManager::install("KEGGlincs")                                             ## LONG install (gcc ...)

R:> install.packages("BiocManager")

  trying URL 'http://cran.stat.sfu.ca/src/contrib/BiocManager_1.30.4.tar.gz'
  Content type 'application/x-gzip' length 242304 bytes (236 KB)
  downloaded 236 KB

  * installing *source* package 'BiocManager' ...
  ** package 'BiocManager' successfully unpacked and MD5 sums checked
  ** using staged installation
  ** R
  ** inst
  ** byte-compile and prepare package for lazy loading
  ** help
  *** installing help indices
  ** building package indices
  ** installing vignettes
  ** testing if installed package can be loaded from temporary location
  ** testing if installed package can be loaded from final location
  ** testing if installed package keeps a record of temporary installation path
  * DONE (BiocManager)

  The downloaded source packages are in
    '/tmp/RtmpVpk0e2/downloaded_packages'

R:> BiocManager::install("KEGGlincs")

  Bioconductor version 3.9 (BiocManager 1.30.4), R 3.6.1 (2019-07-05)
  Installing package(s) 'BiocVersion', 'KEGGlincs'
  also installing the dependencies 'assertthat', 'bit', 'prettyunits', 'digest', 'sys', 'zlibbioc', 'bit64', 'blob', 'memoise', 'BH', 'plogr', 'bitops', 'askpass', 'XVector', 'BiocGenerics', 'Biobase', 'IRanges', 'DBI', 'RSQLite', 'S4Vectors', 'graph', 'RCurl', 'magrittr', 'pkgconfig', 'Rcpp', 'curl', 'jsonlite', 'mime', 'openssl', 'R6', 'png', 'Biostrings', 'KOdata', 'hgu133a.db', 'org.Hs.eg.db', 'AnnotationDbi', 'KEGGgraph', 'igraph', 'plyr', 'gtools', 'httr', 'RJSONIO', 'KEGGREST', 'XML'

  [ ... SNIP! ... ]

  * DONE (KEGGlincs)
  The downloaded source packages are in
    '/tmp/RtmpVpk0e2/downloaded_packages'

R:> browseVignettes("KEGGlincs")
  starting httpd help server ... done                                           ## http://127.0.0.1:26205/library/KEGGlincs/doc/Example-workflow.html

R:>

------------------------------------------------------------------------------

SCRIPT: https://rdrr.io/bioc/KEGGlincs/man/cyto_vis.html
        /mnt/Vancouver/programming/R/scripts/kegg_p53_signaling.R

## R:
library(KEGGlincs)

p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML, FALSE)
nodes <- node_mapping_info(p53_KEGG_mappings)

p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
edges <- edge_mapping_info(p53_edges)

p53_graph_object <- get_graph_object(nodes, edges)

## Not run:
# cyto_vis(graph_object, title = "Cytoscape Graph Window", edge_width_attribute = "summary_score", port.number = 1234)
cyto_vis(p53_graph_object, "Default p53 Graph [no data added]")

#Workflow to visualize graph with data-dependent attributes:

p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML)
nodes <- node_mapping_info(p53_KEGG_mappings)

p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)

p53_HA1E_data <- overlap_info(p53_KGML, p53_KEGG_mappings, "HA1E",
                               data_type = "100_bing")
p53_edges_plus_data <- add_edge_data(p53_edges, p53_KEGG_mappings,
                                      p53_HA1E_data, c(3, 10,12),
                                      only_mapped = TRUE)

edges <- edge_mapping_info(p53_edges_plus_data, data_added = TRUE)

p53_plus_data_graph_object <- get_graph_object(nodes, edges)

cyto_vis(p53_plus_data_graph_object, "p53 Graph: Mapped Edges + HA1E Data",
         edge_width_attribute = "UP")

## End(Not run)

----------------------------------------
# Execution:
#   directly: /mnt/Vancouver/programming/R/scripts/kegg_p53_signaling.R
#    R shell: source("/mnt/Vancouver/programming/R/scripts/kegg_p53_signaling.R")

# NOTE: Cytoscape must be running for cyto_vis() instance to instantiate ...


========================================
KEGGlincs SESSION [2019-07-06]
==============================

R:> browseVignettes("KEGGlincs")
  starting httpd help server ... done                                           ## http://127.0.0.1:26205/library/KEGGlincs/doc/Example-workflow.html

http://127.0.0.1:26205/library/KEGGlincs/doc/Example-workflow.html

R:> FoxO_KGML <- get_KGML("hsa04068")

R:> # Information from KGML can be accessed using the following syntax:
R:> slot(FoxO_KGML, "pathwayInfo")
[ Title ]: FoxO signaling pathway
[ Name ]: path:hsa04068
[ Organism ]: hsa
[ Number ] :04068
[ Image ] :http://www.kegg.jp/kegg/pathway/hsa/hsa04068.png
[ Link ] :http://www.kegg.jp/kegg-bin/show_pathway?hsa04068

R:> # View the original pathway image (get address for pathway with active links):
R:> slot(slot(FoxO_KGML, "pathwayInfo"), "image")
[1] "http://www.kegg.jp/kegg/pathway/hsa/hsa04068.png"

R:> # Download a static pathway image (png file) to working directory:
R:> image_link <- slot(slot(FoxO_KGML, "pathwayInfo"), "image")
R:> download.file(image_link, basename(image_link), mode = "wb")
trying URL 'http://www.kegg.jp/kegg/pathway/hsa/hsa04068.png'
Content type 'image/png' length 36405 bytes (35 KB)
downloaded 35 KB

R:> getwd()
[1] "/mnt/Vancouver/programming/data/metabolism/practice/networkx"

R:> ls()
 [1] "edges"                      "FoxO_KGML"                  "image_link"                 "library"                    "nodes"                      "p53_edges"
 [7] "p53_edges_plus_data"        "p53_graph_object"           "p53_HA1E_data"              "p53_KEGG_mappings"          "p53_KGML"                   "p53_plus_data_graph_object"

R:> dir()
 [1] "_networkx_notes.txt"                      "docs"                                     "glycolysis_nodes_xy.tsv"                  "glycolysis_nodes_xy2_reversed_y.tsv"
 [5] "glycolysis+tca.tsv"                       "holoview_(bokeh)_practice"                "hsa04068.png"                             "mpldatacursor"
 [9] "networkx_practice-03.py"                  "networkx_practice-hover-follow-cursor.py" "pyvis"                                    "test05.csv"
[13] "test05.tsv"                               "test05+code.tsv"                          "versions"


==============================================================================
KEGGscape
=========

* http://keggscape.readthedocs.org/
  A Cytoscape app for importing KGML (KEGG pathway XML)

* How to import KEGG pathway xml (kgml) to Cytoscape
  https://keggscape.readthedocs.io/en/latest/howtouse.html

* A guide to exploring KEGG pathways with KEGGscape
  https://keggscape.readthedocs.io/en/latest/index.html

 ** KEGGscape (Ideker lab) constructs KEGG pathway on Cytoscape3
    https://github.com/idekerlab/KEGGscape

 ** https://github.com/idekerlab/KEGGscape#tutorials
    TUTORIALS!

  *** https://github.com/idekerlab/KEGGscape/wiki/Visualizing-Time-Series-Metabolome-Profiles
      [2014; within Cytoscape] Visualizing Time Series Metabolome Profiles
            [Jupyter notebook] https://nbviewer.jupyter.org/github/idekerlab/cy-rest-python/blob/develop/advanced/CytoscapeREST_KEGG_time_series.ipynb

  *** https://keggscape.readthedocs.io/en/latest/drugtarget.html#mapping-drug-targets-on-kegg-pathway
      Mapping drug targets on KEGG pathway

* QUESTION: ARE KEGG XML (KGML) FILES MISSING FROM WEBSITE?
  https://www.biostars.org/p/160077/
  https://www.biostars.org/p/202663/
  https://www.biostars.org/p/71737/
  https://www.biostars.org/p/57344/

  http://onetipperday.sterding.com/2018/06/download-all-kegg-pathway-kgml-files.html

  [https://github.com/widdowquinn/KGML << deprecated; refers to:]
  https://github.com/biopython/biopython
  https://nbviewer.jupyter.org/github/widdowquinn/notebooks/blob/master/Biopython_KGML_intro.ipynb    ## << cool; some comments in: https://github.com/biopython/biopython/issues/1510

 ** NOTE re: KGML files -- (Glycolysis / Gluconeogenesis) available here          ## genome.jp

      https://www.genome.jp/kegg-bin/show_pathway?hsa00010
      [ Pathway menu | Organism menu | Pathway entry | ***DOWNLOAD KGML***  | Show description | User data mapping ]

    not here                                                                        ## kegg.jp

      https://www.kegg.jp/kegg-bin/show_pathway?org_name=hsadd&mapno=00010&mapscale=&show_description=show
      [ Pathway menu | Hide description | Disease/drug list | User data mapping ]

------------------------------------------------------------------------------

==============================================================================
LITERATURE
==========

* Analysis of Triplet Motifs in Biological Signed Oriented Graphs Suggests a Relationship Between Fine Topology and Function
  https://arxiv.org/pdf/1803.06520.pdf

  Cytoscape App Store: http://apps.cytoscape.org/apps/counttriplets

    The Cytoscape CountTriplets app counts triplets and computes z-scores against randomly generated networks. In addition, it plots significance profiles and lists motifs for each node in the network reporting in a separate column the functional class the protein (node) belongs to (Transcription factor, receptor, phosphatase, kinase) which can be used in further statistical and machine learning studies.


==============================================================================
WEB
===

* Amazing visualizations, including 3D:

 ** https://news.ycombinator.com/item?id=18527104
  *** https://github.com/anvaka/pm
      https://anvaka.github.io/pm/#/?_k=9kvbgq


==============================================================================
==============================================================================
END OF FILE
==============================================================================
==============================================================================