I've seen a lot of tips going around on how to speed up python code or make it more efficient. I've tried some things on the code below like: change global variables to local variables, whenever possible, using .format to create strings instead of adding strings, trying to not create multiple variables. But still, this script takes 1h25 to run. I have two input files:
1) A bed file, two column (tab delimited) file with number or code in the first column, and numbers in the second column. It has ~2 billion lines, where the combination of numbers is unique (it has all the positions in a genome; the first column is the chromosome, the second is the position):
1 1
1 2
1 3
1 4
...
2) a complex file, where the first few (~3000 lines) are a header that start with #, and then an entry for, again, a combination of number/code + number in the first two columns. This two columns make the link with the first file (1 1 in file 1 is the the same as 1 1 in file 2). This has ~22 million of rows. Here is an example of the first three lines:
1 1 . G . 32.9939 . DP=1;MQ0F=0;AF1=0;AC1=0;DP4=1,0,0,0;MQ=60;FQ=-29.9923 GT:PL:GQ 0/1:0:36
1 2 . T . 32.9939 . DP=1;MQ0F=0;AF1=0;AC1=0;DP4=1,0,0,0;MQ=60;FQ=-29.9923 GT:PL:GQ ./.:0:36
1 3 . C . 32.9939 . DP=1;MQ0F=0;AF1=0;AC1=0;DP4=1,0,0,0;MQ=60;FQ=-29.9923 GT:PL:GQ 1/1:0:36
Question: I want to filter rows in the first file, if those rows on the second file have a 0/0, 0/1 or 1/1 (the 4th possibility is ./.) in the last column (so I need to pars the last column, to reach those three characters)
The added complexity is that file #2 has to be read through a pipe from another program because it's compressed in a specific way done by that program (opening this file takes a long time on its own but nothing I can do about it...)
Call: program view file2.vcf.gz | my_script.py file1.bed
import sys
import re
import time
start_time = time.time()
def make_vcf_dict(vcf):
mydict={}
for line in (line for line in vcf if not line.startswith("#")):
line=line.strip().split()
genotype=line[-1].split(':')[0]
motif=re.compile('\./\.')
if motif.match(genotype) is None:
mydict.setdefault('{}:{}'.format(line[0],line[1]),'{}:{}'.format(line[0],line[1]))
return mydict
def create_output_bed(bed,data):
print "creating output"
for line in (line for line in data if line.startswith('#CHROM')):
output_name='{}_mask_positions.bed'.format(line.strip().split()[-1])
print output_name
output=open(output_name,'w')
print "making dictionary"
for line in bed:
line=line.strip().split()
#creating the same entry as in dict:
region='{}:{}'.format(line[0], line[1])
if region not in mydict:
output.write('{}\t{}\n'.format(line[0],line[1]))
output.close()
bed.close()
return
print "reading data"
data=sys.stdin.readlines() #.readlines here is key!!
mydict=make_vcf_dict(data)
#read the bed file:
print "Writing output"
create_output_bed(open(sys.argv[1],'r'),data)
print("--- %s seconds ---" % (time.time() - start_time))
I was wondering if there would be a more efficient way to deal with this entirely? Not making a dictionary, splitting my file? I have a 32 core server to deal with this and little experience with scripting...
Thank you!
If the second file has only a few million rows (not billion as the first), then I expect the data to fit in the memory.
I have a 32 core server to deal with this
Parallelizing it won't help you much because the main bottleneck is the disk, not the CPU. Unless the data was distributed among many files on different disks.
However, you do have some improvements you can make:
Move the regex compilation outside the loop (motif=re.compile('\./\.')).
Use set instead of dict.
Avoid the format, just use a tuple.
Don't read all the lines beforehand.
Avoid going over stdin twice.
Avoid doing anything twice.
import sys
import re
import time
start_time = time.time()
def make_vcf(vcf_input):
output = set()
motif=re.compile('\./\.')
for line in vcf_input:
line = line.strip().split()
if line[0].startswith('#CHROM'):
output_name = '{}_mask_positions.bed'.format(line[-1])
continue
elif line[0].startswith("#"):
continue
genotype=line[-1].split(':')[0]
if motif.match(genotype) is None:
output.add( (line[0],line[1]) )
return output_name, output
def create_output_bed(output_name, vcf, bed):
print "creating output:", output_name
output = open(output_name,'w')
print "making dictionary"
for line in bed:
line = line.strip().split()
#creating the same entry as in dict:
region = line[0], line[1]
if region not in vcf:
output.write('{}\t{}\n'.format(line[0],line[1]))
output.close()
bed.close()
return
print "reading data"
output_name, vcf = make_vcf(sys.stdin.readlines())
#read the bed file:
print "Writing output"
create_output_bed(output_name, vcf, open(sys.argv[1],'r'))
print("--- %s seconds ---" % (time.time() - start_time))
Related
I have a list of 3-gram terms of around 10000 in a .txt file. I want to match these terms within multiple .GHC files under a directory and count the occurrences of each of the terms.
One of these files looks like this:
ntdll.dll+0x1e8bd ntdll.dll+0x11a7 ntdll.dll+0x1e6f4 kernel32.dll+0xaa7f kernel32.dll+0xb50b ntdll.dll+0x1e8bd ntdll.dll+0x11a7 ntdll.dll+0x1e6f4 kernel32.dll+0xaa7f kernel32.dll+0xb50b ntdll.dll+0x1e8bd ntdll.dll+0x11a7 ntdll.dll+0x1e6f4 kernel32.dll+0xaa7f kernel32.dll+0xb50b ntdll.dll+0x1e8bd ntdll.dll+0x11a7 ntdll.dll+0x1e6f4 kernel32.dll+0xaa7f kernel32.dll+0xb50b kernel32.dll+0xb511 kernel32.dll+0x16d4f
I want the resulting output to be like this in a dataframe:
N_gram_term_1 N_gram_term_2 ............ N_gram_term_n
2 1 0
3 2 4
3 0 3
the 2nd line here indicates that N_gram_term_1 has appeared 2 times in one file and N_gram_term_2 1 time and so on.
the 3rd line indicates that N_gram_term_1 has appeared 3 times in second file and N_gram_term_2 2 times and so on.
If I need to be more clear about something, please let me know.
I am sure you have implementations for this purpoes, perhaps in sklearn. A simple implementation from scratch, though would be:
import sys
d = {} # dictionary that will have 1st key = file and 2 key = 3gram
for file in sys.argv[1:]: # These are all files to be analyzed
d[file] = {} # The value here is a nested dictionary
with open(file) as f: # Opening each file at a time
for line in f: # going through every row of the file
g = line.strip()
if g in d[file]:
d[file][g] +=1
else:
d[file][g] = 1
import pandas
print(pandas.DataFrame(d).T)
I have this file containing 82 pairs of IDs:
EmuJ_000063620.1 EgrG_000063620.1 253 253
EmuJ_000065200.1 EgrG_000065200.1 128 128
EmuJ_000081200.1 EgrG_000081200.1 1213 1213
EmuJ_000096200.1 EgrG_000096200.1 295 298
EmuJ_000114700.1 EgrG_000114700.1 153 153
EmuJ_000133800.1 EgrG_000133800.1 153 153
EmuJ_000139900.1 EgrG_000144400.1 2937 2937
EmuJ_000164600.1 EgrG_000164600.1 167 167
and I have two other files with the sequences for EmuJ_* IDs and EgrG_* IDs as follows:
EgrG_sequences.fasta:
>EgrG_000632500.1
MKKKSHRKSPEGNHSLTKAANKDTAKCNEERGRNIGQSNEEENATRSEKDREGDEDRNLREYVISIAQKYYPHLVSCMRQDDDNQASADARGADGANDEEHCPKHCPRLNAQKYYLYSATCNHHCEDSQASCDEEGDGKRLLKQCLLWLTERYYPSLAARIRQCNDDQASSNAHGADETDDGDRRLKQALLLFAKKLYPCVTTCIRHCVADHTSHDARGVDEEVDGEQLLKQCLHSSAQKFYPRLAACVCHCDADHASTETCGALGVGNAERCPQQCPCLCAQQYYVQSATCVHHCDNEQSSPETRGVKEDVDVEQLLKQCLLMFAEKFHPTLAAGIRSCADDESSHVASVEGEDDADKQRLKQYLLLFAQKYYPHLIAYIQKRDDDQSSSSVRDSGEEANEEEERLKQCLLLFAQKLYPRLVAYTGRCDSNQSTSDGCSVDGEEAEKHYLKQSLLLLAQKYYPSLAAYLRQFDDNQSSSDVRSVDEEEAEKRHLKQGLLFFAEKYYPSLATYIRRCDDDQSSSDARVVDEVDDEDRRLKQGLLLLAQKYYPPLANYIRHSQSSFNVCGADEKEDEEHCLNQLPRLCAQEAYIRSSSCSHHCDDDQASNDTLVVDKEEEEKYRLKQGLLLLAQKFYPPLATCIHQCDDQSSHDTRGVDEEEAEEQLLKKCLLMFAEKFYPSLAATIHHSVYDQASFDMRDVDTENDETHCLSLSAENYSTASTTCIHHSDGDQSTSDACGVEEGDVEEQRLKRGLLLLAQKYYPSLAAYICQCDDYQPSSDVCGVGEEDTGEERLKQCLLLFAKKFYPSLASRNSQCGDNLILNDEVVGETVINSDTDTDEVTPVEKSTAVCDEVDEVPFKYVGSPTPLSDVDVDSLEKVIPPNDLTAHSSFQNSLDHSVEGGYPDRAFYIGRHTVESADSTAPLSKSSSTKLYFSNTDEFPTEEEVSSPIAPLSIQRRIRIYLEDLENVRKVSLIPLCKTDKFGNPQEEIIIDSNLDDDTDESKLSSVDVEFTMEQADATPLDLEAQDEDLKNCVAIILKHIWSELMECIRREGLSDVYELSLGDRRIEVPQDDVCLVR*
>EgrG_000006700.1
MTDTKGPDESYFEKEAFSSLPQPVDSPSASATDTDRIPVVAVSLPVSSGSIDVNCNCSCYLIICETKLIIDYQMTRKW*
and so on. The same for EmuJ_sequences.fasta
I need to get the sequences for each pair and write one after the other maintaining the order like this:
>EmuJ_000063620.1
AEPGSGDFDANALRDLANEHQRRVQQKQADLETYELQVLDSVLELTSQLSLNLNEKISKAYENQCRLDTEVKRLCSNIQTFNRQVDMWNKEILDINSALKELGDAETWSQKLCRDVQIIHDTLQAADK*
>EgrG_000063620.1
AEPGSGDFDANALRDLANEHQRRVQQKQADLETYELQVLDSVLELTSQLSLNLNEKISKAYDNQCRLDTEVKRLCSNIQTFNCQVDLWNKEILDINSALKELGDAETWSQKLCRDVQIIHDTLQAADK*
>EmuJ_000065200.1
MLCLITPFPSVVPVCVRTCVCMCPCPLLLILYTWSAYLVPFSLPLCLYAHFHIRFLPPFSSLSIPRFLTHSLFLPSYPPLTMLRMKKSLAPCPAERR*
>EgrG_000065200.1
MLCLVTSFPSAVPVCMRTCVCMCSCPLLLILYTWSAYLVPFSLPLCLYTHLHIRFLPPFPSLAIPRFLTHPLFLPTSLYVADKKEPSAMPRRASLRQMLLIVLLQELH*
>EmuJ_000081200.1
MNSLRIFAVVITCLMVVGFSYSIHPTFPSYQSVVWHSSANTGYECRDGICGYRCSNPWCHGFGSILHPQMGVQEMWGSAAHGRHAHSRAMTEFLAKASPEDVTMLIESTPNIDEVITSLDGEAVTILINKLPNLRRVMEELKPQTKMHIVSKLCGKVGSAMEWTEARRNDGSGMWNEYGSGWEGIDAIQDLEAEVIMRCVQDCGYCAHPTMDGGYVFDPIPIKDVAVYDDSMNWQPQLPTPATSVSSMDPLVLRSIILNMPNLNDILMQVDPVYLQSALVHVPGFGAYASSMDAYTLHSMIVGLPYVRDIVASMDARLLQRMIAHIPNIDAILFGGNAVISQPTMPDMPRKAPRAEEPDAKTTEVAGGMSDEANIMDRKFMEYIISTMPNVPTRFANVLLHVKPDYVRYIIEKHGNLHGLLAKMNAQTLQYVIAHVPKFGVILSNMNRNTLKVVFDKLPNIAKFLADMNPRVVRAIVAKLPSLAKYTPTDPTTTALPTSVTLVPELGTEFSSYAATASATEEPTVTVDYANLLRSKIPLIDNVIKMSDPEKVAILRDNLLDVSRILVNLDPTMLRNINSIIFNATKMLNELSVFLVEYPLEYLHKEGKSGVAVNKSEQVGTTGENGVSSIAVEKLQMVLLKIPLFDQFLKWIDQKKLHELLNKIPTLLEVIATANQETLDKINSLLHDAIATMNTAKKLIVTGICRKLAEEGKLRLPRVCPSAST*
>EgrG_000081200.1
MNLLRIFAVVITCLIVVGFGYPTHPTFPSYQTAVWHSSANTGYRCRAGICGYRCSSPWCHGFESALYPQMAMQEMWGSGAHGRHAHSRTMTEFLMKASPEDLTMLIESTPNIDEVITSLDSEAIIILINKLPNLRRVMEKLKPQTKMHIVSKLCDKVGNAMEWAGARRNDGSGMWNEYGSVWEGIDAIQDLEAEMITRCVQDCGYCAHPTMDGGYVFDPIPIKDVAVYDDSMNWQPQLPMPATLVSNMDPHVLRSIILNMPNLDDILMQVDPVHLQSALMYVPGFGTYASSMDAYTLHSMIVGLPYVRDIVASMDARLLQWMIAHIPNIDAILFGGNAVISQPTMPDMPRKAPKAEEPDAKTTEVAGGMSDEANIMDRKFMEYIISTMPNVPARFANVLLHVKPDYVRYIIENHGNLHGLLAKMNAQTLQYVIAHVPKFGVILSNMNRNTLKVVFDKLPNIAKFLADMNPNVVRAIVAKLPSLAKYTPTDPTTTALPTSVTLVPELGTEFSSYAPTASVTEASMVTVDYAHLLRSKIPLIDNVIKMSDPAKVAILRDNLLDVGTTDENGVSSITVEKLQMVLLKIPLFDQFLNWIDSKKLHALLQKIPTLLEVIATANQEALDKINLLLHDAIATMNTAKKLIVTSICRKLAEEGKLRLPRVCPSTST*
And so on.
I wrote a script in bash to do this and it worked like I wanted, it was very simple. Now I'm trying to do the same in Python (which I'm learning), but I'm having a hard time to do the same in a pythonic way.
I've tried this, but I've got only the first pair and then it stopped:
rbh=open('rbh_res_eg-not-sec.txt', 'r')
ems=open('em_seq.fasta', 'r')
egs=open('eg_seq.fasta', 'r')
for l in rbh:
emid=l.split('\t')[0]
egid=l.split('\t')[1]
# ids=emid+'\n'+egid
# print ids # just to check if split worked
for lm in ems:
if emid in lm:
print lm.strip()
print next(ems).strip()
for lg in egs:
if egid in lg:
print lg.strip()
print next(egs).strip()
I've tried some variations but I've got only the IDs, without the sequences.
So, how can I find the ID in the sequence file, print it and the line after it (the line with sequence referring to the ID)?
Please, let me know if I explained it clearly.
Iterating over a file moves the file pointer until it reaches the end of the file (the last line), so after the first iteration of your outer loop, the ems and egs files are exhausted.
The quick&dirty workaround would be to reset the ems and egs pointers to zero at the end of the outer loop, ie:
for line in rbh:
# no need to split twice
parts = line.split("\t")
emid, egid = parts[0].strip(), parts[1].strip()
for lm in ems:
if emid in lm:
print lm.strip()
print next(ems).strip()
ems.seek(0) # reset the file pointer
for lg in egs:
if egid in lg:
print lg.strip()
print next(egs).strip()
egs.seek(0) # reset the file pointer
Note that calling next(iterator) while already iterating over iterator will consume one more item of the iterator, as illustrated here:
>>> it = iter(range(20))
>>> for x in it:
... print x, next(it)
...
0 1
2 3
4 5
6 7
8 9
10 11
12 13
14 15
16 17
18 19
As you can see, we don't iter on each element of our range here... Given your file format it should not be a huge problem but I thought I'd still warn you about it.
Now your algorithm is far from efficient - for each line of the rbh file it will read scan the whole ems and egs files again and again.
_NB : the following assumes that each emid / egid will appear at most once in the fasta files._
If your ems and egs files are not too large and you have enough available memory, you could load them into a pair of dicts and do a mere dict lookup (which is O(1) and possibly one of the most optimized operation in Python)
# warning: totally untested code
def fastamap(path):
d = dict()
with open(path) as f:
for num, line in enumerate(f, 1):
line = line.strip()
# skip empty lines.
if not line:
continue
# sanity check: we should only see
# lines starting with ">", the "value"
# lines being consumed by the `next(f)` call
if not line.startswith(">"):
raise ValueError(
"in file %s: line %s doesn't start with '>'" % (
path, num
))
# ok, proceed
d[line.lstrip(">")] = next(f).strip()
return d
ems = fastamap('em_seq.fasta')
egs = fastamap('eg_seq.fasta')
with open('rbh_res_eg-not-sec.txt') as rhb:
for line in rhb:
parts = line.split("\t")
emid, egid = parts[0].strip(), parts[1].strip()
if emid in ems:
print emid
print ems[emid]
if egid in egs:
print egid
print egs[egid]
If this doesn't fly because of memory issues, well bad luck you're stuck with sequential scan (unless you want to use some database system but this might be a bit overkill), but - always assuming the emid/egid each only appears once in the fasta files - you can at least exit the inner loops once you've find your target:
for l in rbh:
# no need to split twice, you can just unpack
emid, egid = l.split('\t')
for lm in ems:
if emid in lm:
print lm.strip()
print next(ems).strip()
break # no need to go further
ems.seek(0) # reset the file pointer
# etc...
I have a bunch of data in .txt file and I need it in a format that I can use in fusion tables/spreadsheet. I assume that that format would be a csv that I can write into another file that I can then import into a spreadsheet to work with.
The data is in this format with multiple entries separated by a blank line.
Start Time
8/18/14, 11:59 AM
Duration
15 min
Start Side
Left
Fed on Both Sides
No
Start Time
8/18/14, 8:59 AM
Duration
13 min
Start Side
Right
Fed on Both Sides
No
(etc.)
but I need it ultimately in this format (or whatever i can use to get it into a spreadsheet)
StartDate, StartTime, Duration, StartSide, FedOnBothSides
8/18/14, 11:59 AM, 15, Left, No
- , -, -, -, -
The problems I have come across are:
-I don't need all the info or every line but i'm not sure how to automatically separate them. I don't even know if the way I am going about sorting each line is smart
-I have been getting an error that says that "argument 1 must be string or read-only character buffer, not list" when I use .read() or .readlines() sometimes (although it did work at first). also both of my arguments are .txt files.
-the dates and times are not in set formats with regular lengths (it has 8/4/14, 5:14 AM instead of 08/04/14, 05:14 AM) which I'm not sure how to deal with
this is what I have tried so far
from sys import argv
from os.path import exists
def filework():
script, from_file, to_file = argv
print "copying from %s to %s" % (from_file, to_file)
in_file = open(from_file)
indata = in_file.readlines() #.read() .readline .readlines .read().splitline .xreadlines
print "the input file is %d bytes long" % len(indata)
print "does the output file exist? %r" % exists(to_file)
print "ready, hit RETURN to continue, CTRL-C to abort."
raw_input()
#do stuff section----------------BEGIN
for i in indata:
if i == "Start Time":
pass #do something
elif i== '{date format}':
pass #do something
else:
pass #do something
#do stuff section----------------END
out_file = open(to_file, 'w')
out_file.write(indata)
print "alright, all done."
out_file.close()
in_file.close()
filework()
So I'm relatively unversed in scripts like this that have multiple complex parts. Any help and suggestions would be greatly appreciated. Sorry if this is a jumble.
Thanks
This code should work, although its not exactly optimal, but I'm sure you'll figure out how to make it better!
What this code basically does is:
Get all the lines from the input data
Loop through all the lines, and try to recognize different keys (the start time etc)
If a keys is recognize, get the line beneath it, and apply a appropriate function to it
If a new line is found, add the current entry to a list, so that other entries can be read
Write the data to a file
Incase you haven't seen string formatting being done this way before:
"{0:} {1:}".format(arg0, arg1), the {0:} is just a way of defining a placeholder for a variable(here: arg0), and the 0 just defines which arguments to use.
Find out more here:
Python .format docs
Python OrderedDict docs
If you are using a version of python < 2.7, you might have to install a other version of ordereddicts by using pip install ordereddict. If that doesn't work, just change data = OrderedDict() to data = {}, and it should work. But then the output will look somewhat different each time it is generated, but it will still be correct.
from sys import argv
from os.path import exists
# since we want to have a somewhat standardized format
# and dicts are unordered by default
try:
from collections import OrderedDict
except ImportError:
# python 2.6 or earlier, use backport
from ordereddict import OrderedDict
def get_time_and_date(time):
date, time = time.split(",")
time, time_indic = time.split()
date = pad_time(date)
time = "{0:} {1:}".format(pad_time(time), time_indic)
return time, date
"""
Make all the time values look the same, ex turn 5:30 AM into 05:30 AM
"""
def pad_time(time):
# if its time
if ":" in time:
separator = ":"
# if its a date
else:
separator = "/"
time = time.split(separator)
for index, num in enumerate(time):
if len(num) < 2:
time[index] = "0" + time[index]
return separator.join(time)
def filework():
from_file, to_file = argv[1:]
data = OrderedDict()
print "copying from %s to %s" % (from_file, to_file)
# by using open(...) the file closes automatically
with open(from_file, "r") as inputfile:
indata = inputfile.readlines()
entries = []
print "the input file is %d bytes long" % len(indata)
print "does the output file exist? %r" % exists(to_file)
print "ready, hit RETURN to continue, CTRL-C to abort."
raw_input()
for line_num in xrange(len(indata)):
# make the entire string lowercase to be more flexible,
# and then remove whitespace
line_lowered = indata[line_num].lower().strip()
if "start time" == line_lowered:
time, date = get_time_and_date(indata[line_num+1].strip())
data["StartTime"] = time
data["StartDate"] = date
elif "duration" == line_lowered:
duration = indata[line_num+1].strip().split()
# only keep the amount of minutes
data["Duration"] = duration[0]
elif "start side" == line_lowered:
data["StartSide"] = indata[line_num+1].strip()
elif "fed on both sides" == line_lowered:
data["FedOnBothSides"] = indata[line_num+1].strip()
elif line_lowered == "":
# if a blank line is found, prepare for reading a new entry
entries.append(data)
data = OrderedDict()
entries.append(data)
# create the outfile if it does not exist
with open(to_file, "w+") as outfile:
headers = entries[0].keys()
outfile.write(", ".join(headers) + "\n")
for entry in entries:
outfile.write(", ".join(entry.values()) + "\n")
filework()
So the question basically gives me 19 DNA sequences and wants me to makea basic text table. The first column has to be the sequence ID, the second column the length of the sequence, the third is the number of "A"'s, 4th is "G"'s, 5th is "C", 6th is "T", 7th is %GC, 8th is whether or not it has "TGA" in the sequence. Then I get all these values and write a table to "dna_stats.txt"
Here is my code:
fh = open("dna.fasta","r")
Acount = 0
Ccount = 0
Gcount = 0
Tcount = 0
seq=0
alllines = fh.readlines()
for line in alllines:
if line.startswith(">"):
seq+=1
continue
Acount+=line.count("A")
Ccount+=line.count("C")
Gcount+=line.count("G")
Tcount+=line.count("T")
genomeSize=Acount+Gcount+Ccount+Tcount
percentGC=(Gcount+Ccount)*100.00/genomeSize
print "sequence", seq
print "Length of Sequence",len(line)
print Acount,Ccount,Gcount,Tcount
print "Percent of GC","%.2f"%(percentGC)
if "TGA" in line:
print "Yes"
else:
print "No"
fh2 = open("dna_stats.txt","w")
for line in alllines:
splitlines = line.split()
lenstr=str(len(line))
seqstr = str(seq)
fh2.write(seqstr+"\t"+lenstr+"\n")
I found that you have to convert the variables into strings. I have all of the values calculated correctly when I print them out in the terminal. However, I keep getting only 19 for the first column, when it should go 1,2,3,4,5,etc. to represent all of the sequences. I tried it with the other variables and it just got the total amounts of the whole file. I started trying to make the table but have not finished it.
So my biggest issue is that I don't know how to get the values for the variables for each specific line.
I am new to python and programming in general so any tips or tricks or anything at all will really help.
I am using python version 2.7
Well, your biggest issue:
for line in alllines: #1
...
fh2 = open("dna_stats.txt","w")
for line in alllines: #2
....
Indentation matters. This says "for every line (#1), open a file and then loop over every line again(#2)..."
De-indent those things.
This puts the info in a dictionary as you go and allows for DNA sequences to go over multiple lines
from __future__ import division # ensure things like 1/2 is 0.5 rather than 0
from collections import defaultdict
fh = open("dna.fasta","r")
alllines = fh.readlines()
fh2 = open("dna_stats.txt","w")
seq=0
data = dict()
for line in alllines:
if line.startswith(">"):
seq+=1
data[seq]=defaultdict(int) #default value will be zero if key is not present hence we can do +=1 without originally initializing to zero
data[seq]['seq']=seq
previous_line_end = "" #TGA might be split accross line
continue
data[seq]['Acount']+=line.count("A")
data[seq]['Ccount']+=line.count("C")
data[seq]['Gcount']+=line.count("G")
data[seq]['Tcount']+=line.count("T")
data[seq]['genomeSize']+=data[seq]['Acount']+data[seq]['Gcount']+data[seq]['Ccount']+data[seq]['Tcount']
line_over = previous_line_end + line[:3]
data[seq]['hasTGA']= data[seq]['hasTGA'] or ("TGA" in line) or (TGA in line_over)
previous_line_end = str.strip(line[-4:]) #save previous_line_end for next line removing new line character.
for seq in data.keys():
data[seq]['percentGC']=(data[seq]['Gcount']+data[seq]['Ccount'])*100.00/data[seq]['genomeSize']
s = '%(seq)d, %(genomeSize)d, %(Acount)d, %(Ccount)d, %(Tcount)d, %(Tcount)d, %(percentGC).2f, %(hasTGA)s'
fh2.write(s % data[seq])
fh.close()
fh2.close()
I have a program where I take a pair of very large multiple sequence files (>77,000 sequences each averaging about 1000 bp long) and calculate the alignment score between each paired individual element and write that number into an output file (which I will load into an excel file later).
My code works for small multiple sequence files but my large master file will throw the following traceback after analyzing the 16th pair.
Traceback (most recent call last):
File "C:\Users\Harry\Documents\cgigas\BioPython Programs\Score Create Program\scoreCreate", line 109, in <module>
cycle(f,k,binLen)
File "C:\Users\Harry\Documents\cgigas\BioPython Programs\Score Create Program\scoreCreate", line 85, in cycle
a = pairwise2.align.localxx(currentSubject.seq, currentQuery.seq, score_only=True)
File "C:\Python26\lib\site-packages\Bio\pairwise2.py", line 301, in __call__
return _align(**keywds)
File "C:\Python26\lib\site-packages\Bio\pairwise2.py", line 322, in _align
score_only)
MemoryError: Out of memory
I have tried many things to work around this (as many of you may see from the code), all to no avail. I have tried splitting the large master file into smaller batches to be fed into score calculating method. I have tried del files after I am done using them, I have tried using my Ubuntu 11.11 on an Oracle Virtual machine (I typically work in 64bit Windows 7). Am I being to ambitious is this computationally feasable in BioPython? Below is my code, I have no experience in memory debugging which is the clear culprit of this problem. Any assistance is greatly appreciated I am becoming very frustrated with this problem.
Best,
Harry
##Open reference file
##a.)Upload subjectList
##b.)Upload query list (a and b are pairwise data)
## Cycle through each paired FASTA and get alignment score of each(Large file)
from Bio import SeqIO
from Bio import pairwise2
import gc
##BATCH ITERATOR METHOD (not my code)
def batch_iterator(iterator, batch_size) :
entry = True #Make sure we loop once
while entry :
batch = []
while len(batch) < batch_size :
try :
entry = iterator.next()
except StopIteration :
entry = None
if entry is None :
#End of file
break
batch.append(entry)
if batch :
yield batch
def split(subject,query):
##Query Iterator and Batch Subject Iterator
query_iterator = SeqIO.parse(query,"fasta")
record_iter = SeqIO.parse(subject,"fasta")
##Writes both large file into many small files
print "Splitting Subject File..."
binLen=2
for j, batch1 in enumerate(batch_iterator(record_iter, binLen)) :
filename1="groupA_%i.fasta" % (j+1)
handle1=open(filename1, "w")
count1 = SeqIO.write(batch1, handle1, "fasta")
handle1.close()
print "Done splitting Subject file"
print "Splitting Query File..."
for k, batch2 in enumerate(batch_iterator(query_iterator,binLen)):
filename2="groupB_%i.fasta" % (k+1)
handle2=open(filename2, "w")
count2 = SeqIO.write(batch2, handle2, "fasta")
handle2.close()
print "Done splitting both FASTA files"
print " "
return [k ,binLen]
##This file will hold the alignment scores in a tab deliminated text
f = open("C:\\Users\\Harry\\Documents\\cgigas\\alignScore.txt", 'w')
def cycle(f,k,binLen):
i=1
m=1
while i<=k+1:
##Open the first small file
subjectFile = open("C:\\Users\\Harry\\Documents\\cgigas\\BioPython Programs\\groupA_" + str(i)+".fasta", "rU")
queryFile =open("C:\\Users\\Harry\\Documents\\cgigas\\BioPython Programs\\groupB_" + str(i)+".fasta", "rU")
i=i+1
j=0
##Make small file iterators
smallQuery=SeqIO.parse(queryFile,"fasta")
smallSubject=SeqIO.parse(subjectFile,"fasta")
##Cycles through both sets of FASTA files
while j<binLen:
j=j+1
currentQuery=smallQuery.next()
currentSubject=smallSubject.next()
##Verify every pair is correct
print " "
print "Pair: " + str(m)
print "Subject: "+ currentSubject.id
print "Query: " + currentQuery.id
gc.collect()
a = pairwise2.align.localxx(currentSubject.seq, currentQuery.seq, score_only=True)
gc.collect()
currentQuery=None
currentSubject=None
score=str(a)
a=None
print "Score: " + score
f.write("1"+ "\n")
m=m+1
smallQuery.close()
smallSubject.close()
subjectFile.close()
queryFile.close()
gc.collect()
print "New file"
##MAIN PROGRAM
##Here is our paired list of FASTA files
##subject = open("C:\\Users\\Harry\\Documents\\cgigas\\subjectFASTA.fasta", "rU")
##query =open("C:\\Users\\Harry\\Documents\\cgigas\\queryFASTA.fasta", "rU")
##[k,binLen]=split(subject,query)
k=272
binLen=2
cycle(f,k,binLen)
P.S. Be kind I am aware there is probably some goofy things in the code that I put in there trying to get around this problem.
See also this very similar question on BioStars, http://www.biostars.org/post/show/45893/trying-to-get-around-memoryerror-out-of-memory-exception-in-biopython-program/
There I suggested trying existing tools for this kind of thing, e.g. EMBOSS needleall http://emboss.open-bio.org/wiki/Appdoc:Needleall (you can parse the EMBOSS alignment output with Biopython)
The pairwise2 module was updated in the recent version of Biopython (1.68) to become faster and less memory consuming.