The most straightforward approach is to use the substr()
function:
% time perl -e '$/ = \1048576;
while ($s = <>) { for $i (0..length $s) {
$hash{ substr($s, $i, 5) }++ } }
foreach my $k (sort { $hash{$b} <=> $hash{$a} } keys %hash) {
print "$k $hash{$k}\n"; $it++; last if $it == 5;}' nucleotide.data
NNCTA 337530
GNGGA 337362
NCACT 337304
GANGN 337290
ACGGC 337210
269.79 real 268.92 user 0.66 sys
The Perl Monks node on iterating along a string was a useful resource, as were the responses and comments from @Jonathan Leffler, @ÆvarArnfjörðBjarmason, @Vorsprung, @ThisSuitIsBlackNotm @borodin and @ikegami here in this SO posting. As was pointed out, the issue with very large files is memory, which in turn requires that files be read in chunks. When reading from a file in chunks, if your code is iterating through the data it has to properly handle switching from one chunk/source to the next without dropping any bytes.
As a simplistic example, next unless length $kmer == 5;
will get checked during each 1048576
byte/character iteration in the script above, meaning strings that exist at the end of one chunk and the beginning of another will be missed (cf. @ikegami's and @Borodin's solutions). This will alter the resulting count, though perhaps not in a statistically significant way[1]. Both @borodin and @ikegami address the issue of missing/overlapping strings between chunks by appending each chunk to the remaining characters of the previous chunk as they sysread
in their while()
loops. See Borodin's response and comments for an explanation of how it works.
Using Stream::Reader
Since perl has been around for quite a while and has collected a lot of useful code, another perfectly valid approach is to look for a CPAN module that achieves the same end. Stream::Reader
can create a "stream" interface to a file handle that wraps the solution to the chunking issue behind a set of convenient functions for accessing the data.
use Stream::Reader;
use strict;
use warnings;
open( my $handler, "<", shift );
my $stream = Stream::Reader->new( $handler, { Mode => "UB" } );
my %hash;
my $string;
while ($stream->readto("\n", { Out => \$string }) ) {
foreach my $i (0..length $string) {
$hash{ substr($string, $i, 5) }++
}
}
my $it;
foreach my $k (sort { $hash{$b} <=> $hash{$a} } keys %hash ) {
print "$k $hash{$k}\n";
$it++; last if $it == 5;
}
On a test data file nucleotide.data
, both Borodin's script and the Stream::Reader
approach shown above produced the same top five results. Note the small difference compared to the results from the shell command above. This illustrates the need to properly handle reading data in chunks.
NNCTA 337530
GNGGA 337362
NCACT 337305
GANGN 337290
ACGGC 337210
The Stream::Reader
based script was significantly faster:
time perl sequence_search_stream-reader.pl nucleotide.data
252.12s
time perl sequence_search_borodin.pl nucleotide.data
350.57s
The file nucleotide.data
was a 1Gb in size, consisting of single string of approximately 1 billion characters:
% wc nucleotide.data
0 0 1048576000 nucleotide.data
% echo `head -c 20 nucleotide.data`
NCCANGCTNGGNCGNNANNA
I used this command to create the file:
perl -MString::Random=random_regex -e '
open (my $fh, ">>", "nucleotide.data");
for (0..999) { print $fh random_regex(q|[GCNTA]{1048576}|) ;}'
Lists and Strings
Since the application is supposed to read a chunk at a time and move this $seq_length
sized window along the length of the data building a hash for tracking string frequency, I thought a "lazy list" approach might work here. But, to move a window through a collection of data (or slide
as with List::Gen
) reading elements natatime
, one needs a list.
I was seeing the data as one very long string which would first have to be made into a list for this approach to work. I'm not sure how efficient this can be made. Nevertheless, here is my attempt at a "lazy list" approach to the question:
use List::Gen 'slide';
$/ = \1048575; # Read a million character/bytes at a time.
my %hash;
while (my $seq = <>) {
chomp $seq;
foreach my $kmer (slide { join("", @_) } 5 => split //, $seq) {
next unless length $kmer == 5;
$hash{$kmer}++;
}
}
foreach my $k (sort { $hash{$b} <=> $hash{$a} } keys %hash) {
print "$k $hash{$k}\n";
$it++; last if $it == 5;
}
I'm not sure this is "typical perl" (TIMTOWDI of course) and I suppose there are other techniques (cf. gather/take
) and utilities suitable for this task. I like the response from @Borodin best since it seems to be the most common way to take on this task and is more efficient for the potentially large file sizes that were mentioned (100Gb).
Is there a fast/best way to turn a string into a list or object? Using an incremental read()
or sysread()
with substr
wins on this point, but even with sysread
a 1000Gb string would require a lot of memory just for the resulting hash. Perhaps a technique that serialized/cached the hash to disk as it grew beyond a certain size would work with very, very large strings that were liable to create very large hashes.
Postscript and Results
The List::Gen
approach was consistently between 5 and 6 times slower than @Borodin's approach. The fastest script used the Stream::Reader
module. Results were consistent and each script selected the same top five strings with the two smaller files:
1 million character nucleotide string
sequence_search_stream-reader.pl : 0.26s
sequence_search_borodin.pl : 0.39s
sequence_search_listgen.pl : 2.04s
83 million character nucleotide string
With the data in file xaa
:
wc xaa
0 1 83886080 xaa
% time perl sequence_search_stream-reader.pl xaa
GGCNG 31510
TAGNN 31182
AACTA 30944
GTCAN 30792
ANTAT 30756
21.33 real 20.95 user 0.35 sys
% time perl sequence_search_borodin.pl xaa
GGCNG 31510
TAGNN 31182
AACTA 30944
GTCAN 30792
ANTAT 30756
28.13 real 28.08 user 0.03 sys
% time perl sequence_search_listgen.pl xaa
GGCNG 31510
TAGNN 31182
AACTA 30944
GTCAN 30792
ANTAT 30756
157.54 real 156.93 user 0.45 sys
1 billion character nucleotide string
In a larger file the differences were of similar magnitude but, because as written it does not correctly handle sequences spanning chunk boundaries, the List::Gen
script had the same discrepancy as the shell command line at the beginning of this post. The larger file meant a number of chunk boundaries and a discrepancy in the count.
sequence_search_stream-reader.pl : 252.12s
sequence_search_borodin.pl : 350.57s
sequence_search_listgen.pl : 1928.34s
The chunk boundary issue can of course be resolved, but I'd be interested to know about other potential errors or bottlenecks that are introduced using a "lazy list" approach. If there were any benefit in terms of CPU usage from using slide
to "lazily" move along the string, it seems to be rendered moot by the need to make a list out of the string before starting.
I'm not surprised that reading data across chunk boundaries is left as an implementation exercise (perhaps it cannot be handled "magically") but I wonder what other CPAN modules or well worn subroutine style solutions might exist.
1. Skipping four characters - and thus four 5 character string combinations - at the end of each megabyte read of a terabyte file would mean the results would not include 3/10000
of 1%
from the final count.
echo "scale=10; 100 * (1024^4/1024^2 ) * 4 / 1024^4 " | bc
.0003814697