我有一个变化表（variation.txt），这是一个非常大的文件。在染色体数目和第二列中的第一列是变化的位置。我有有37,000个基因的列表（第1列），它们的染色体数目（第2列），他们的起点和终点坐标（第3列），第二个文件annotation.txt，其次是一些细节
我必须分配的变化（基于染色体数目和其位置）的基因。首先，它应该在这两个文件中匹配的染色体数目，如果匹配，该变化的坐标应为内（含）开始，该基因的末端位置。我曾在蟒蛇尝试，但它需要很长时间。此外，我想有一个修改的输出，如下所示。基因可以具有重叠的坐标和给定的变化可以是多种重叠基因的一部分。请帮助。
variation.txt
SL3.0ch02 702679 C A - - - - - - - -
SL3.0ch01 711131 A G - - - - - - - -
SL3.0ch00 715124 G A - - - - - - - -
SL3.0ch00 719289 C T - - - - - - - -
SL3.0ch00 720926 A C - - - - - - - -
SL3.0ch00 723860 A C Solyc00g005060.1 CDS NONSYNONYMOUS W/G 52 0 novel DELETERIOUS (*WARNING! Low confidence)
SL3.0ch00 723867 A C Solyc00g005060.1 CDS SYNONYMOUS G/G 49 1 novel TOLERATED
SL3.0ch00 723903 T C Solyc00g005060.1 CDS SYNONYMOUS G/G 37 1 novel TOLERATED
annotation.txt
Solyc00g005000.3.1 SL3.0ch02 702600 702900 + Eukaryotic aspartyl protease family protein
Solyc00g005040.3.1 SL3.0ch01 715100 715200 + Potassium channel
Solyc00g005050.3.1 SL3.0ch00 715150 715300 - UPF0664 stress-induced protein C29B12.11c
Solyc00g005060.1.1 SL3.0ch00 723741 724013 - LOW QUALITY:Cyclin/Brf1-like TBP-binding protein
Solyc00g005080.2.1 SL3.0ch00 723800 723900 - LOW QUALITY:Protein Ycf2
Solyc00g005084.1.1 SL3.0ch05 809593 813633 + UDP-Glycosyltransferase superfamily protein
Solyc00g005090.1.1 SL3.0ch07 1061632 1061916 - LOW QUALITY:DYNAMIN-like 1B
Solyc00g005092.1.1 SL3.0ch01 1127794 1144385 + Serine/threonine phosphatase-like protein
Solyc00g005094.1.1 SL3.0ch00 1144958 1146952 - Glucose-6-phosphate 1-dehydrogenase 3, chloroplastic
Solyc00g005096.1.1 SL3.0ch00 1734562 1736567 + RWP-RK domain-containing protein
所需的输出：
SL3.0ch02 702679 C A - - - - - - - - Solyc00g005000.3.1
SL3.0ch00 715124 G A - - - - - - - - Solyc00g005040.3.1
SL3.0ch00 723860 A C Solyc00g005060.1 CDS NONSYNONYMOUS W/G 52 0 novel DELETERIOUS (*WARNING! Low confidence) Solyc00g005060.1.1
SL3.0ch00 723860 A C Solyc00g005060.1 CDS NONSYNONYMOUS W/G 52 0 novel DELETERIOUS (*WARNING! Low confidence) Solyc00g005080.2.1
SL3.0ch00 723867 A C Solyc00g005060.1 CDS SYNONYMOUS G/G 49 1 novel TOLERATED Solyc00g005060.1.1
SL3.0ch00 723867 A C Solyc00g005060.1 CDS SYNONYMOUS G/G 49 1 novel TOLERATED Solyc00g005080.2.1
SL3.0ch00 723903 T C Solyc00g005060.1 CDS SYNONYMOUS G/G 37 1 novel TOLERATED Solyc00g005060.1.1
码：
import re
file1 = open("variation", "r")
file2 = open("annotation.txt", "r")
probe_id = file1.read().splitlines()
loc_id = file2.read().splitlines()
for i in probe_id:
i=i.rstrip()
probe_info=i.split('\t')
probe_info[1]=probe_info[1].strip()
probe_info[0]=probe_info[0].strip()
#print probe_info[1]
gene_list=[]
for j in loc_id:
loc_info=j.split('\t')
loc_info[2]=loc_info[2].strip()
loc_info[3]=loc_info[3].strip()
if loc_info[1]==probe_info[0]:
if (int(probe_info[1]) >= int(loc_info[2])):
if (int(probe_info[1]) <=int(loc_info[3])):
gene_list.append(loc_info[0])
if len(gene_list)!=0:
print i+"\t"+str(gene_list)
电流输出：
SL3.0ch02 702679 C A - - - - - - - - ['Solyc00g005000.3.1']
SL3.0ch00 715124 G A - - - - - - - - ['Solyc00g005040.3.1']
SL3.0ch00 723860 A C Solyc00g005060.1 CDS NONSYNONYMOUS W/G 52 0 novel DELETERIOUS (*WARNING! Low confidence) ['Solyc00g005060.1.1', 'Solyc00g005080.2.1']
SL3.0ch00 723867 A C Solyc00g005060.1 CDS SYNONYMOUS G/G 49 1 novel TOLERATED ['Solyc00g005060.1.1', 'Solyc00g005080.2.1']
SL3.0ch00 723903 T C Solyc00g005060.1 CDS SYNONYMOUS G/G 37 1 novel TOLERATED ['Solyc00g005060.1.1']
这是GNU AWK相匹配的染色体数目和范围内的位置开始：
$ awk '
NR==FNR {
a[$2][$3 " " $4]=$0 # store the annotations
next
}
($1 in a){ # if chromosome found
for(i in a[$1]) # process all the ranges
if(split(i,t)&&$2>=t[1]&&$2<=t[2]) # if there is a match
print # output
}' anno vari
输出ATM：
SL3.0ch02 702679 C A - - - - - - - -
SL3.0ch00 723860 A C Solyc00g005060.1 CDS NONSYNONYMOUS W/G 52 0 novel DELETERIOUS (*WARNING! Low confidence)
SL3.0ch00 723860 A C Solyc00g005060.1 CDS NONSYNONYMOUS W/G 52 0 novel DELETERIOUS (*WARNING! Low confidence)
SL3.0ch00 723867 A C Solyc00g005060.1 CDS SYNONYMOUS G/G 49 1 novel TOLERATED
SL3.0ch00 723867 A C Solyc00g005060.1 CDS SYNONYMOUS G/G 49 1 novel TOLERATED
SL3.0ch00 723903 T C Solyc00g005060.1 CDS SYNONYMOUS G/G 37 1 novel TOLERATED
这将是有效的前处理“annotation.txt”，并创建一个字典提前，以减少循环计算。 请尝试以下方法：
#!/usr/bin/python
import re
file1 = open("variation.txt", "r")
file2 = open("annotation.txt", "r")
probe_id = file1.read().splitlines()
loc_id = file2.read().splitlines()
annotation = {}
for i in loc_id:
loc_info=i.split('\t')
gene = loc_info[0].strip()
chromosome = loc_info[1].strip()
start = int(loc_info[2].strip())
end = int(loc_info[3].strip())
if (chromosome in annotation.keys()):
annotation[chromosome].append([start, end, gene])
else:
annotation[chromosome] = [[start, end, gene]]
for i in probe_id:
i = i.rstrip()
probe_info = i.split('\t')
position = int(probe_info[1].strip())
chromosome = probe_info[0].strip()
if (chromosome in annotation.keys()):
for j in annotation[chromosome]:
if (j[0] <= position and position <= j[1]):
print i + '\t' + j[2]
输出：
SL3.0ch02 702679 C A - - - - - - - - Solyc00g005000.3.1
SL3.0ch00 723860 A C Solyc00g005060.1 CDS NONSYNONYMOUS W/G 52 0 novel DELETERIOUS (*WARNING! Low confidence) Solyc00g005060.1.1
SL3.0ch00 723860 A C Solyc00g005060.1 CDS NONSYNONYMOUS W/G 52 0 novel DELETERIOUS (*WARNING! Low confidence) Solyc00g005080.2.1
SL3.0ch00 723867 A C Solyc00g005060.1 CDS SYNONYMOUS G/G 49 1 novel TOLERATED Solyc00g005060.1.1
SL3.0ch00 723867 A C Solyc00g005060.1 CDS SYNONYMOUS G/G 49 1 novel TOLERATED Solyc00g005080.2.1
SL3.0ch00 723903 T C Solyc00g005060.1 CDS SYNONYMOUS G/G 37 1 novel TOLERATED Solyc00g005060.1.1
我想，该算法主要是接近@詹姆斯布朗的回答。 希望这可以帮助。