Merge pull request #3 from labgem/dev

Update Readme et fix writting graphML

README.md

@@ -1,60 +1,45 @@
+[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/netsyn/README.html)
+[![installs](https://img.shields.io/conda/dn/bioconda/netsyn.svg?style=flag&label=BioConda%20install)](https://anaconda.org/bioconda/netsyn)
+
 # NetSyn: detect synteny conservation among a list of protein targets
 
 NetSyn is a tool to detect conserved genomic contexts (i.e. synteny conservation) among a set of protein (call protein targets). Synteny are computed using a re-implementation of the method described in Boyer *et al.* article ([https://doi.org/10.1093/bioinformatics/bti711](https://doi.org/10.1093/bioinformatics/bti711)).
 
 ## Installation
 
-Prerequisites: python 3.8 and MMseqs2.
-
-Netsyn installation: `python3 setup.py install`
-
-For the installation of MMseqs2 please refer to https://github.com/soedinglab/MMseqs2/wiki#installation
-
- Python library list:
-
-  - pyyaml
 
-  - igraph
+### Installation with BioConda
 
-  - jsonschema
+Netsyn can be easilly installed with bioconda
 
-  - networkx (>= 2.8)
+```bash 
 
-  - markov_clustering
+conda create -n netsyn -c bioconda netsyn
 
-  - urllib3
 
-  - biopython
-
-  - requests
-
-You can easely install NetSyn using an virtual environment with pip (command lines example below):
-
-  - virtualenv venv_netsyn
+```
 
-  - source venv_netsyn/bin/activate
 
-  - pip install pyyaml
+### Manual installation
 
-  - pip install igraph
+You can easely install NetSyn with pip. Netsyn requires python >= 3.8
 
-  - pip install jsonschema
+```bash
 
-  - pip install networkx
+git clone https://github.com/labgem/netsyn
 
-  - pip install markov_clustering
+pip install netsyn/
 
-  - pip install urllib3
+```
 
-  - git clone https://github.com/labgem/netsyn
+Netsyn requires MMseqs2 as a 3rd party software which must be installed and executable. For the installation of MMseqs2 please refer to https://github.com/soedinglab/MMseqs2/wiki#installation
 
-  - python3 setup.py install
 
 ## Basic Usage
 
 NetSyn can be used with 2 different input file formats. One is a file containing a list of UniProt accessions (`-u` option), while the other one is a correspondences file (`-c` option). The two types of file are described in the Input Data part. It is possible to start an analysis with both input file formats. It leads to 3 NetSyn basic usage callings:
 
-  - with the UniProt accessions list:
+  - with the UniProt accessions list: 
     `netsyn -u <UniProtAC.list> -o <OutputDirName>`
 
   - with the correspondences file:

netsyn/netsyn_dataExport.py

@@ -9,6 +9,7 @@
 import logging
 import os
 import igraph as ig
+import networkx as nx
 import re
 #############
 # Functions #
@@ -638,7 +639,11 @@ def run(nodesFile, edgesFile, organismsFile, proteinsFile, metadataFile, redunda
 
     mergeResultIntoHTML(
         htmlOut, common.global_dict['htmlTemplate'], common.global_dict['jsTemplate'], netsynResult)
-    full_graph.write_graphml(graphmlOut)
+
+    # full_graph.write_graphml(graphmlOut)
+    logger.debug('Writting graphML output...')
+    full_graph_nx = full_graph.to_networkx()
+    nx.write_graphml_lxml(full_graph_nx, graphmlOut, named_key_ids=True)
 
     # COM: Storage of information to write ClusteringSynthesis files
     logger.info('Analysis synthesis process...')

setup.py

@@ -20,18 +20,19 @@
         'pyyaml',
         'python-igraph',
         'jsonschema',
-        'networkx',
+        'networkx>=2.8',
         'markov_clustering',
         'urllib3',
         'biopython',
+        'requests'
     ],
 
     include_package_data=True,
 
     url='http://github.com/labgem/netsyn',
 
     classifiers=[
-        'Programming Language :: Python :: 3.7',
+        'Programming Language :: Python :: 3.8',
         'License :: OSI Approved :: CEA CNRS Inria Logiciel Libre License, version 2.1 (CeCILL-2.1)',
         'Topic :: Scientific/Engineering :: Bio-Informatics'
     ],