mirror of
https://github.com/Priyatham-sai-chand/compara-deep-learning.git
synced 2026-10-05 08:11:34 -07:00
76 lines
2 KiB
Python
76 lines
2 KiB
Python
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import numpy as np
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import os
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import json
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from read_data import read_data_homology
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import matplotlib.pyplot as plt
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import seaborn as sns
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a_h,_=read_data_homology("data_homology")
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ndir="processed/synteny_matrices/"
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nf1="synteny_matrices_global_"
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nf2="synteny_matrices_local_"
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nf3="indexes_"
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lsy={}
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with open("processed/neighbor_genes.json","r") as file:
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lsy=dict(json.load(file))
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synteny_matrices_global=np.load(ndir+nf1+"11"+".npy")
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synteny_matrices_local=np.load(ndir+nf2+"11"+".npy")
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indexes=np.load(ndir+nf3+"11"+".npy")
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df=a_h[0].loc[indexes]
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inddict={}
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for i in range(len(indexes)):
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inddict[indexes[i]]=i
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while(1):
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i=int(input("Enter the index"))
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if i in inddict:
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print("Species",df.loc[i].species)
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print("Homology Species",df.loc[i].homology_species)
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print("Gene Stable Id:",df.loc[i].gene_stable_id)
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print("Homology Gene Stable Id:",df.loc[i].homology_gene_stable_id)
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print("Global aligned matrix:")
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g1=df.loc[i].gene_stable_id
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g2=df.loc[i].homology_gene_stable_id
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x=[]
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y=[]
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for n in range(len(lsy[g1]['b'])-1,-1,-1):
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x.append(lsy[g1]['b'][n])
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x.append(g1)
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for k in lsy[g1]['f']:
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x.append(k)
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for n in range(len(lsy[g2]['b'])-1,-1,-1):
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y.append(lsy[g2]['b'][n])
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y.append(g2)
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for k in lsy[g2]['f']:
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y.append(k)
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loc=inddict[i]
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sg=synteny_matrices_global[loc]
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sl=synteny_matrices_local[loc]
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for m in range(sg.shape[-1]):
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matrix=sg[:,:,m]
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print(matrix)
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hmap=sns.heatmap(matrix,xticklabels=y, yticklabels=x,annot=True)
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plt.show()
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print("Local Alignment Matrix")
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for m in range(sg.shape[-1]):
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matrix=sl[:,:,m]
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print(matrix)
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hmap=sns.heatmap(matrix,xticklabels=y, yticklabels=x,annot=True)
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plt.show()
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else:
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print("Index not found")
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