genetic-tree

implementation of a script in python that takes in input a file containing a list of mutations and a file containing a matrix of 0 and 1 associated to the species (rows) and generates a random phylogenetic tree import sys import random import math from anytree import Node, RenderTree from deap import base , creator , tools

#Lettura del file matrix in input file_rows=[] with open(sys.argv[1],'r') as input_file: for s in input_file: file_rows.append(s.split())

list_tree={} mutations=[] #label_node={} #dizionario={} #Lettura del file mutations in input with open(sys.argv[2], 'r') as input_file: for s in input_file: mutations.append(s.strip()) #dizionario[random.randint(1,1000)]=s.strip()

def tree(root): d={} dizionario={} for i in mutations: dizionario[random.randint(1,1000)]=i keys_ordered=sorted(dizionario.keys()) parent1=root #parent1=Node("root", parent=None) d[0]=parent1 cont=0 cont1=1 for i in keys_ordered: if(cont<2): parent2=Node(dizionario[i],parent=parent1) cont=cont+1 d[cont1]=parent2 if(cont==2): cont=0 parent1=d[int(cont1/2)] cont1=cont1+1 list_tree[root.name]=d print(RenderTree(d[0]))

def vista_albero(): print(list_tree.keys()) root=input('scegli il nome dell albero da visualizzare') return list_tree[root]

def attach_node(x): if(list_tree=={}): return print("PRIMA SI GENERI L ALBERO") tmp=vista_albero() print("key node") for i in tmp.keys(): print(i, tmp[i]) new_node=input('seleziona la key del nodo padre')

new_m=input('inserisci il nome della nuova mutazione')

    if x=='3':
            new_m=input('inserisci la key della nuova mutazione')
            if (tmp[int(new_m)] in tmp[int(new_node)].ancestors or
             tmp[int(new_m)]== tmp[int(new_node)]):
                    return print("non è possibile ,mutazione già presente")
            node=Node(tmp[int(new_m)].name, parent=tmp[int(new_node)])
    elif x=='5':
            new_m=input('inserisci la key della nuova mutazione')
            if(tmp[int(new_m)] in tmp[int(new_node)].ancestors or
            tmp[int(new_m)]==tmp[int(new_node)]):
                    return print("non è possibile,mutazione già presente")
            figli=tmp[int(new_node)].children
            node=Node(tmp[int(new_m)].name)
            tmp[int(new_node)].children=[node]
            for i in figli:
                    i.parent=node
    elif x=='2':
            mutation=input('inserisci la key della mutazione da eliminare')
            node=Node("-"+tmp[int(mutation)].name,parent=tmp[int(new_node)])

print(node.name)

    elif x=='6':
            mutation=input('inserire la key della mutazione da eliminare')
            figli=tmp[int(new_node)].children
            node=Node("-"+tmp[int(mutation)].name)
            tmp[int(new_node)].children=[node]
            for i in figli:
                    i.parent=node

    tmp[len(tmp)]=node

def path_mutation(): #array=[] if list_tree=={}: return print("PRIMA SI GENERI L ALBERO") tmp=vista_albero() print("key node") for i in tmp.keys(): print(i, tmp[i]) index_node=input("seleziona la key del nodo") return path(tmp[int(index_node)])

def path(node): array=[] antenati=node.ancestors m=[] m.append(node.name) for i in antenati: m.append(i.name) for j in mutations: if (j in m) and not("-"+j in m): array.append(1) elif "-"+j in m and j in m: array.append(0) elif "-"+j in m and not(j in m): array.append(-1) else : array.append(0) #print(mutations) #print(m) return array

alfa=0.15 beta=0.001 def evaluate(individual,name,tree): leafs=[] res={} for i in tree.values(): if(i.is_leaf): leafs.append(i) for leaf in leafs: likelihood=0 i=path(leaf) #print(i) for j in range(len(individual)): if individual[j] == '0': if i[j] == 0: likelihood+=math.log10(1-beta) elif i[j] == 1: likelihood+=math.log10(beta) elif i[j] == -1: return print("error, perdita mutazione non esistente") elif individual[j] == '1': if i[j] == 0: likelihood+=math.log10(1-alfa) elif i[j] == 1: likelihood+=math.log10(alfa) elif i[j] == -1: return print("error perdita mutazione non esistente") elif individual[j]== '2': likelihood+=0 res[likelihood]=leaf

if res.keys==[]:

return print("error", individual)

print(res.keys())

    a=max(res.keys())

print(risultato)

print(res[risultato])

    Node(name,parent=res[a])
    #return risultato

likelihood_tree={} def val_likelihood(): for i in likelihood_tree.keys(): print(i,likelihood_tree[i]) val=input('seleziona key') print(likelihood_tree[int(val)]) #parte di codice con la libreria deap a while True: #control=input('seleziona un opzione : ') print("likelihood alberi : 0") print("generare albero : 1") print("eliminare nodo : 2") print("inserire nodo : 3") print("mostra lista degli alberi : 4") print("inserisci un nodo intermedio : 5") print("elimina un nodo intermedio : 6") print("mostra path array : 7") print("valutare albero : 8") print("exit : n") control=input('seleziona un opzione : ') if control=='n': break elif control=='1': name=input('inserisci il nome della radice') tree(Node(name,parent=None)) elif control=='2': attach_node(control) elif control=='3': attach_node(control) elif control=='4': rst=vista_albero() print(RenderTree(rst[0])) elif control=='5': attach_node(control) elif control=='6': attach_node(control) elif control=='7': ris=path_mutation() print(ris) elif control=='8': tmp=vista_albero() for i in range(57): evaluate(file_rows[i],i,tmp) print(tmp[0].name) # likelihood_tree[tmp[0].name]=likelihood elif control=='9': print(file_rows[11]) elif control=='0': val_likelihood()