Created
November 18, 2017 06:35
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| def is_nuc(nuc): | |
| try: | |
| n1, n2 = nuc.split(':') | |
| if not n1 in 'ATGC' and n2 in 'ATGC': | |
| return np.nan | |
| else: | |
| return nuc | |
| except: | |
| return np.nan | |
| def nuc_combinations(nuc1, nuc2): | |
| nuc1, nuc2 = is_nuc(nuc1), is_nuc(nuc2) | |
| try: | |
| return list(set([':'.join(sorted([n1, n2])) | |
| for n1 in nuc1.split(':') | |
| for n2 in nuc2.split(':')])) | |
| except: return np.nan; | |
| def cartesian_coord(*arrays): | |
| grid = np.meshgrid(*arrays) | |
| coord_list = [entry.ravel() for entry in grid] | |
| points = np.vstack(coord_list).T | |
| return points | |
| def cross(parent1, parent2): | |
| possibilities = [nuc_combinations(nuc1, nuc2) | |
| for nuc1, nuc2 in zip(parent1, parent2)] | |
| return cartesian_coord(*possibilities) | |
| @mem.cache | |
| def simulate_all_crosses(df, hybrid, parent_groups = ['female', 'male']): | |
| data = df[df['hybrid'] == hybrid] | |
| snps = [c for c in df.columns if 'snp' in c] | |
| parents1 = data[data['type'] == parent_groups[0]][snps].values | |
| parents2 = data[data['type'] == parent_groups[1]][snps].values | |
| offsprings = [] | |
| for comb in tqdm(product(parents1, parents2), leave=False): | |
| try: | |
| offsprings += cross(*comb).tolist() | |
| except: | |
| print(comb) | |
| offsprings = pd.DataFrame(offsprings, columns=snps) | |
| offsprings = offsprings.drop_duplicates() | |
| offsprings['hybrid'] = hybrid | |
| if parent_groups[0] != parent_groups[1]: | |
| offsprings['status'] = 'hybrid' | |
| else: | |
| offsprings['status'] = 'inbred' | |
| #add the actual data | |
| return offsprings |
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