#!/usr/bin/env python
# coding: utf-8

# # Protein-Protein interaction (PPI) analysis by String-db
# STRING is a database of known and predicted protein-protein interactions. The interactions include direct (physical) and indirect (functional) associations; they stem from computational prediction, from knowledge transfer between organisms, and from interactions aggregated from other (primary) databases.
# 
# Here we produce a tutorial that use python to construct protein-protein interaction network
# 
# Colab_Reproducibility：https://colab.research.google.com/drive/1ReLCFA5cNNcem_WaMXYN9da7W0GN4gzl?usp=sharing

# In[1]:


import omicverse as ov
ov.utils.ov_plot_set()


# ## Prepare data
# 
# Here we use the example data of string-db to perform the analysis 
# 
# FAA4 and its ten most confident interactors.
# FAA4 in yeast is a long chain fatty acyl-CoA synthetase; see it connected to other synthetases as well as regulators.
# 
# Saccharomyces cerevisiae
# NCBI taxonomy Id: 4932
# Other names: ATCC 18824, Candida robusta, NRRL Y-12632, S. cerevisiae, Saccharomyces capensis, Saccharomyces italicus, Saccharomyces oviformis, Saccharomyces uvarum var. melibiosus, lager beer yeast, yeast

# In[2]:


gene_list=['FAA4','POX1','FAT1','FAS2','FAS1','FAA1','OLE1','YJU3','TGL3','INA1','TGL5']


# Besides, we also need to set the gene's type and color. Here, we randomly set the top 5 genes named Type1, other named Type2

# In[3]:


gene_type_dict=dict(zip(gene_list,['Type1']*5+['Type2']*6))
gene_color_dict=dict(zip(gene_list,['#F7828A']*5+['#9CCCA4']*6))


# ## STRING interaction analysis
# 
# The network API method also allows you to retrieve your STRING interaction network for one or multiple proteins in various text formats. It will tell you the combined score and all the channel specific scores for the set of proteins. You can also extend the network neighborhood by setting "add_nodes", which will add, to your network, new interaction partners in order of their confidence.

# In[7]:


G_res=ov.bulk.string_interaction(gene_list,4932)
G_res.head()


# ## STRING PPI network 
# 
# We also can use `ov.bulk.pyPPI` to get the PPI network of `gene_list`, we init it at first

# In[5]:


ppi=ov.bulk.pyPPI(gene=gene_list,
                      gene_type_dict=gene_type_dict,
                      gene_color_dict=gene_color_dict,
                      species=4932)


# Then we connect to string-db to calculate the protein-protein interaction

# In[8]:


ppi.interaction_analysis()


# We provided a very simple function to plot the network, you can refer the `ov.utils.plot_network` to find out the parameter

# In[9]:


ppi.plot_network()


# In[ ]: