python新手写了个低配版中心法则：）

# central dogma

FILE = "seq5.fasta"

output = open("central_dogma_report.txt", "w")  # 报告文档

# 解析提取fasta格式中纯序列：real_seq
with open(FILE, 'r') as fp:
    real_seq = ''
    for line in fp.readlines():
        if line.startswith('>'):
            seq_name = line
            output.write(seq_name)  # 序列名
        else:
            real_seq += line
    output.write("DNA:\n%s" % real_seq)  # 序列本体
    real_seq = real_seq.replace('\n', '')
    fp.close()

# 统计碱基组成
nt_count = []
for nt in "ATCG":
    nt_count.append(real_seq.count(nt))
A, T, C, G = nt_count[0:4]
others = len(real_seq) - A - T - C - G

output.write("\nseq_length:%d\n" % (A + C + T + G + others))
output.write("nt_composition:\n"
             "A:%d(%.2f%%)\n"
             "T:%d(%.2f%%)\n"
             "C:%d(%.2f%%)\n"
             "G:%d(%.2f%%)\n"
             "others:%d(%.2f%%)"
             % (A, (A / len(real_seq)) * 100,
                T, (T / len(real_seq)) * 100,
                C, (C / len(real_seq)) * 100,
                G, (G / len(real_seq)) * 100,
                others, others / len(real_seq) * 100))  # 碱基组成
output.write("\nGC:%.2f%%\n" % (((C + G) / len(real_seq)) * 100))

# 转录获得mRNA
transcript_table = {'A': 'U', 'T': 'A',
                    'C': 'G', 'G': 'C',
                    'R': '(A/G)', 'Y': '(T/C)',
                    'W': '(A/T)', 'S': '(C/G)',
                    'M': '(A/C)', 'K': '(G/T)',
                    'B': '(C/G/T)', 'D': '(A/G/T)',
                    'H': '(A/C/T)', 'V': '(A/C/G)',
                    'N': '(A/T/C/G)'}
mRNA = ''
for nt in real_seq.upper():
    mRNA += transcript_table[nt]

output.write("mRNA:\n")
for index in range(0, len(mRNA), 70):
    output.write(mRNA[index:index + 70])
    output.write("\n")

# 解析密码子和翻译以及计数氨基酸个数
translate_table = {
    'GCU': 'A', 'GCC': 'A', 'GCA': 'A', 'GCG': 'A', 'CGU': 'R', 'CGC': 'R',
    'CGA': 'R', 'CGG': 'R', 'AGA': 'R', 'AGG': 'R', 'UCU': 'S', 'UCC': 'S',
    'UCA': 'S', 'UCG': 'S', 'AGU': 'S', 'AGC': 'S', 'AUU': 'I', 'AUC': 'I',
    'AUA': 'I', 'UUA': 'L', 'UUG': 'L', 'CUU': 'L', 'CUC': 'L', 'CUA': 'L',
    'CUG': 'L', 'GGU': 'G', 'GGC': 'G', 'GGA': 'G', 'GGG': 'G', 'GUU': 'V',
    'GUC': 'V', 'GUA': 'V', 'GUG': 'V', 'ACU': 'T', 'ACC': 'T', 'ACA': 'T',
    'ACG': 'T', 'CCU': 'P', 'CCC': 'P', 'CCA': 'P', 'CCG': 'P', 'AAU': 'N',
    'AAC': 'N', 'GAU': 'D', 'GAC': 'D', 'UGU': 'C', 'UGC': 'C', 'CAA': 'Q',
    'CAG': 'Q', 'GAA': 'E', 'GAG': 'E', 'CAU': 'H', 'CAC': 'H', 'AAA': 'K',
    'AAG': 'K', 'UUU': 'F', 'UUC': 'F', 'UAU': 'Y', 'UAC': 'Y', 'AUG': 'M',
    'UGG': 'W', 'UAG': 'STOP', 'UGA': 'STOP', 'UAA': 'STOP'}

output.write("\naa_seq:\n")
for ORF in range(3):
    orf = ''
    output.write("\nORF%d:" % (ORF + 1))
    for index in range(ORF, len(mRNA), 3):
        codon = mRNA[index:index + 3]
        if codon in translate_table.keys():
            if translate_table[codon] == "STOP":
                orf += '*'
            else:
                orf += translate_table[codon]
        else:
            orf += '-'

    for index in range(0, len(orf), 60):
        output.write("\n%s" % (orf[index:index + 60]))
    output.write("\naa number:\n")
    for amino_acid in "ACDEFGHIKLMNPQRSTVWY*-":
        output.write("%s:%d;" % (amino_acid, orf.count(amino_acid)))

output.close()