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今天开始所有的工作脚本全都从perl转变到python,开发速度明显降低了不少,相信以后随着熟练度提升会好起来。贴一下今天一个工作代码,由于之前去一家小公司测序时,序列长度竟然都没有达到要求,为了之后的索赔事宜,写了个脚本统计所有序列的结果,主要包括总的reads数,bases数,和达到测序策略要求长度的reads数(双端),bases数,高质量(Q30)bases数,高质量reads数(双端)等等......多个文件的统计工作一般会写一个单独处理一个文件的脚本,然后再写一个脚本用来生成多个文件的处理的shell脚本,然后想办法并行处理这个shell就可以,效率会快很多。由于测序数据往往比较大,IO操作时,逐行读取是上策。
统计单个文件测序数据情况脚本:
1 from __future__ import division
2 from Bio import SeqIO as fq
3 import os
4 import sys
5 import re
6 read1_gzfile = sys.argv[1]
7 read2_gzfile = sys.argv[2]
8 gz_handle1 = os.popen( 'gunzip -cd %s' % read1_gzfile )
9 gz_handle2 = os.popen( 'gunzip -cd %s' % read2_gzfile )
10 basename1 = os.path.basename(read1_gzfile)
11 basename1 = re.match('(\S+)_R1_001\.fastq\.gz',basename1).group(1)
12 basename2 = os.path.basename(read2_gzfile)
13 basename2 = re.match('(\S+)_R2_001\.fastq\.gz',basename2).group(1)
14 if basename1 != basename2:
15 raise 'Two Read are not mapped!'
16 cwd = os.getcwd()
17 out_handle = open('%s/%s.stat'%(cwd,basename1),'w')
18 out_handle.write('AllReadsNum\tRead1_PE300_ReadsNum\tRead2_PE300_ReadsNum\tUseful_ReadsNum(Read1>=300 and Read2>=300)\tAll_Bases\tRead1_Q30_Bases(PE300)\tRead2_Q30_Bases(PE300)\tQ30_PE_Reads(Q30>50%)\tUseful_Bases(All)\tUseful_Ratio\n')
19
20 AllReadsNum = 0
21 AllBases = 0
22 Read1_PE300_ReadsNum = 0
23 Read2_PE300_ReadsNum = 0
24 Useful_ReadsNum = 0
25 Read1_Q30_Bases = 0
26 Read2_Q30_Bases = 0
27 Q30_PE_Reads = 0
28 Useful_Bases = 0
29
30 def PE300(seq):
31 if len(seq) >= 300:
32 return True
33 else:
34 return False
35
36 def Q30(qual_list):
37 num = 0
38 for qual in qual_list:
39 if qual >= 30:
40 num += 1
41 return num
42
43 reads2 = fq.parse(gz_handle2,'fastq')
44 for read1 in fq.parse(gz_handle1,'fastq'):
45 read2 = reads2.next()
46 seq1 = read1.seq
47 qual1 = read1.letter_annotations['phred_quality']
48 seq2 = read2.seq
49 qual2 = read2.letter_annotations['phred_quality']
50 AllReadsNum += 1
51 AllBases += len(seq1)
52 AllBases += len(seq2)
53 R1_300 = PE300(seq1)
54 R2_300 = PE300(seq2)
55 if R1_300 and R2_300:
56 Useful_ReadsNum +=1
57 R1_Q30 = Q30(qual1)
58 R2_Q30 = Q30(qual2)
59 Read1_Q30_Bases += R1_Q30
60 Read2_Q30_Bases += R2_Q30
61 if ( R1_Q30 / len(seq1) >= 0.5 ) and ( R2_Q30 / len(seq2) >= 0.5 ):
62 Q30_PE_Reads += 1
63 Useful_Bases += R1_Q30
64 Useful_Bases += R2_Q30
65 elif R1_300:
66 Read1_PE300_ReadsNum += 1
67 elif R2_300:
68 Read2_PE300_ReadsNum += 1
69
70 Useful_Ratio = Useful_Bases / AllBases
71 out_handle.write('%i\t%i\t%i\t%i\t%i\t%i\t%i\t%i\t%i\t%f\n'%(AllReadsNum,Read1_PE300_ReadsNum,Read2_PE300_ReadsNum,Useful_ReadsNum,AllBases,Read1_Q30_Bases,Read2_Q30_Bases,Q30_PE_Reads,Useful_Bases,Useful_Ratio))
summary.py 生成脚本:
1 import os
2 out = open('summary.sh','w')
3 cwd = os.getcwd()
4 with open('templist') as gzfiles:
5 for gzfile1 in gzfiles:
6 gzfile2 = gzfiles.next()
7 out.write('python %s/summary.py %s %s\n'%(cwd,gzfile1.strip(),gzfile2.strip()))
run_summary.py 使用qsub_sge方法,并行投递生成的summary.sh就完成了 |
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