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本节内容：
- pssm生成
- pssm简化
- 标准的pssm构建
- 滑动pssm生成
在基于蛋白质序列的相关预测中，使用PSSM打分矩阵会得将预测效果大大提高，同时，如果使用滑动的PSSM，效果又会进一步提高。这里主要以分享代码为主，下面介绍下PSSM从生成到处理的全过程。
1.PSSM的生成
PSSM的生成有多种方式，这里使用的psiblast软件，ncbi-blast-2.2.28+/bin/psiblast，下载地址：http://blast.ncbi.nlm.nih.gov/Blast.cgi?CMD=Web&PAGE_TYPE=BlastNews#1 使用方法，输入一个序列，加上相关参数，直接输出PSSM文件
代码
#一个命令函数，根据pdb文件，使用blast生成pssm文件
def command_pssm(content, output_file,pssm_file):
os.system(‘/ifs/share/lib/blast/ncbi-blast-2.2.28+/bin/psiblast -query %s -db /ifs/data/database/blast_data/nr -num_iterations 3 -out %s -out_ascii_pssm %s &‘ %(content, output_file,pssm_file))上面是执行的命令，封装成函数，下面为实际代码：
#对每个序列进行PSSM打分
def pssm(proseq,outdir):
inputfile = open(proseq,‘r‘)
content = ‘‘
input_file = ‘‘
output_file = ‘‘
pssm_file = ‘‘
chain_name = []
for eachline in inputfile:
if ‘>‘ in eachline:
if len(content):
temp_file = open(outdir + ‘/fasta/‘ + chain_name,‘w‘)
temp_file.write(content)
input_file = outdir + ‘/fasta/‘ + chain_name
output_file = outdir + ‘/‘ + chain_name + ‘.out‘
pssm_file = outdir + ‘/‘ + chain_name + ‘.pssm‘
command_pssm(input_file, output_file,pssm_file)
temp_file.close
content = ‘‘
chain_name = eachline[1:5] + eachline[6:7]
content += ‘‘.join(eachline)
#print content
#print chain_name
if len(content):
temp_file = open(outdir + ‘/fasta/‘ + chain_name,‘w‘)
temp_file.write(content)
input_file = outdir + ‘/fasta/‘ + chain_name
output_file = outdir + ‘/‘ + chain_name + ‘.out‘
pssm_file = outdir + ‘/‘ + chain_name + ‘.pssm‘
command_pssm(input_file, output_file,pssm_file)
temp_file.close
inputfile.close() 测试用例：
‘‘‘
#生成pssm文件，迭代次数为3
proseq = ‘/ifs/home/liudiwei/experiment/step2/data/protein.seq‘
outdir = ‘/ifs/home/liudiwei/experiment/step2/pssm‘
pssm(proseq,outdir)
‘‘‘PSSM输出样例：
2.简化PSSM数据
通常我们需要的只是前面的20列
下面通过代码来实现上面的功能：
#格式化pssm每行数据
def formateachline(eachline):
col = eachline[0:5].strip()
col += ‘\t‘ + eachline[5:8].strip()
begin = 9
end = begin +3
for i in range(20):
begin = begin
end = begin + 3
col += ‘\t‘ + eachline[begin:end].strip()
begin = end
col += ‘\n‘
return col简化pssm，只要得到前面的20个氨基酸的打分值
def simplifypssm(pssmdir,newdir):
listfile = os.listdir(pssmdir)
for eachfile in listfile:
with open(pssmdir + ‘/‘ + eachfile,‘r‘) as inputpssm:
with open(newdir + ‘/‘ + eachfile,‘w‘) as outfile:
count = 0
for eachline in inputpssm:
count +=1
if count <= 3:
continue
if not len(eachline.strip()):
break
oneline = formateachline(eachline)
outfile.write(‘‘.join(oneline))
‘‘‘ Test example
pssmdir = ‘/ifs/home/liudiwei/experiment/step2/pssm/oldpssm‘
newdir = ‘/ifs/home/liudiwei/experiment/step2/pssm/newpssm‘
simplifypssm(pssmdir, newdir)
‘‘‘3.得到标准的PSSM
通过上面抽取出来的PSSM，下面通过代码来获得一个滑动的PSSM
#标准的pssm,直接根据标准的pssm滑动
def standardPSSM(window_size,pssmdir,outdir):
listfile = os.listdir(pssmdir)
for eachfile in listfile:
outfile = open(outdir + ‘/‘ + eachfile, ‘w‘)
with open(pssmdir + ‘/‘ + eachfile, ‘r‘) as inputf:
inputfile = inputf.readlines()
for linenum in range(len(inputfile)):
content = []
first = [];second = [];third=[];last=[]
if linenum < window_size/2:
for i in range((window_size/2 - linenum)*20):
second.append(‘\t0‘)
if window_size/2 - linenum > 0:
countline = window_size - (window_size/2 - linenum)
else:
countline = window_size #get needed line count
linetemp = 0
for eachline in inputfile:
if linetemp < linenum-window_size/2:
linetemp += 1
continue
if linetemp == linenum:
thisline = eachline.split(‘\t‘)
for j in range(0,2):
if j>0:
first.append(‘\t‘)
first.append(thisline[j].strip())
if countline > 0:
oneline = eachline.split(‘\t‘)
for j in range(2,len(oneline)):
third.append(‘\t‘ + oneline[j].strip())
countline -=1
else:
break
linetemp += 1
while countline:
for i in range(20):
last.append(‘\t0‘)
countline -=1
content += first + second + third + last
outfile.write(‘‘.join(content) + ‘\n‘)
outfile.close()
‘‘‘Test example
pssmdir = ‘/ifs/home/liudiwei/experiment/step2/pssm/newpssm‘
newdir = ‘/ifs/home/liudiwei/experiment/step2/pssm/standardpssm‘
window_size = 5
standardPSSM(window_size,pssmdir, newdir)
‘‘‘4.根据滑动窗口求出滑动的PSSM
#根据窗口大小,计算出滑动后的20个氨基酸打分值
def computedPSSM(window_size,pssmdir,outdir):
listfile = os.listdir(pssmdir)
for eachfile in listfile:
outfile = open(outdir + ‘/‘ + eachfile, ‘w‘)
with open(pssmdir + ‘/‘ + eachfile, ‘r‘) as inputf:
inputfile = inputf.readlines()
for linenum in range(len(inputfile)):
content = []
first = [];second = []
if window_size/2 - linenum > 0:
countline = window_size - (window_size/2 - linenum)
else:
countline = window_size #get needed line count
linetemp = 0
for eachline in inputfile:
if linetemp < linenum-window_size/2:
linetemp += 1
continue
if linetemp == linenum:
thisline = eachline.split(‘\t‘)
for j in range(0,2):
if j>0:first.append(‘\t‘)
first.append(thisline[j].strip())
if countline > 0:
oneline = eachline.split(‘\t‘)[2:len(eachline)]
tline = []
for i in range(len(oneline)):
tline.append(int(oneline[i]))
if len(second)==0:
second += tline
else:
second = list(map(lambda x: x[0]+x[1], zip(second, tline)))
countline -=1
else:
break
linetemp += 1
format_second = []
for i in range(len(second)):
format_second.append(‘\t‘ + str(second[i]))
content += first + format_second
outfile.write(‘‘.join(content) + ‘\n‘)
outfile.close()
‘‘‘
pssmdir = ‘/ifs/home/liudiwei/experiment/step2/pssm/newpssm‘
newdir = ‘/ifs/home/liudiwei/experiment/step2/pssm/computedpssm‘
window_size = 5
computedPSSM(window_size,pssmdir, newdir)
‘‘‘平滑的PSSM，只是pssmdir不同，直接调用standardPSSM函数
def smoothedPSSM(window_size,pssmdir,outdir):
standardPSSM(window_size,pssmdir, outdir)
‘‘‘Test example
pssmdir = ‘/ifs/home/liudiwei/experiment/step2/pssm/computedpssm‘
newdir = ‘/ifs/home/liudiwei/experiment/step2/pssm/smoothedpssm‘
window_size = 5
smoothedPSSM(window_size,pssmdir,newdir)
‘‘‘最后得到的是一个滑动的PSSM矩阵，特征的维数随窗口的大小逐渐增减。
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时间： 2024-10-13 20:36:05