mirror of
https://github.com/Priyatham-sai-chand/compara-deep-learning.git
synced 2026-10-05 08:11:34 -07:00
57 lines
1.9 KiB
Python
57 lines
1.9 KiB
Python
import pandas as pd
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import numpy as np
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import os
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import sys
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import progressbar
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import json
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import sys
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from neighbor_genes import read_genome_maps
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from process_data import create_data_homology_ls
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from threads import Procerssrunner
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from read_get_gene_seq import read_gene_sequences
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from access_data_rest import update_rest
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from prepare_synteny_matrix import read_data_synteny
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from save_data import write_dict_json
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def read_database_txt(filename):
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df=pd.read_csv(filename,sep="\t",header=None)
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df=df.drop(0,axis=1)
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df.columns=["gene_stable_id","species","homology_gene_stable_id","homology_species","wga","goc","homology_type"]
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return df
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def main():
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arg=sys.argv
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a,d,ld,ldg,cmap,cimap=read_genome_maps()
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print("Genome Maps Loaded.")
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df=read_database_txt(arg[-2])
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nop=int(arg[-1])
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print("Data Read.")
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a_h=[]
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d_h=[]
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a_h.append(df)
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d_h.append(arg[-2].split(".")[0])
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n=3
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lsy=create_data_homology_ls(a_h,d_h,n,a,d,ld,ldg,cmap,cimap,0)
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write_dict_json("neighbor_genes_negative","processed",lsy)
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print("Neighbor Genes Found and Saved Successfully:)")
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gene_sequences=read_gene_sequences(a_h,lsy,"geneseq","gene_seq_negative")
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gene_sequences=update_rest(gene_sequences,"gene_seq_negative")
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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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for i in range(len(a_h)):
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df=a_h[i]
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part=len(df)//nop
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pr=Procerssrunner()
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pr.start_processes(nop,df,gene_sequences,lsy,part,n,d_h[i])
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smg,sml,indexes=read_data_synteny(nop,d_h[i])
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print(len(indexes))
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np.save(ndir+str(d_h[i])+"_"+nf1,smg)
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np.save(ndir+str(d_h[i])+"_"+nf2,sml)
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np.save(ndir+str(d_h[i])+"_"+nf3,indexes)
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print("Synteny Matrices Created Successfully :)")
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if __name__=="__main__":
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main()
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