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Re: Memory issue with cancer data (analogy)

by BrowserUk (Pope)
on Jul 25, 2013 at 16:51 UTC ( #1046390=note: print w/ replies, xml ) Need Help??


in reply to Memory issue with cancer data (analogy)

Your analogy doesn't help.

You are constructing a 3-dimensional array, and you are running out of memory. Assuming $data[ 0..X ][ 0..Y ][ 0..Z ];

What we need from you is:

  1. the maximum size of those three dimensions X, Y, Z?
  2. Are the dimensions contiguous or sparse?

    If sparse, the approximate density?

    If one or more of X,Y & Z can run say 3000 .. 4000; or if instead of using every number between 0 ..m; you only use every 10th or 100th; then you can save substantial space by using a hash instead of an array for that dimension of the structure.

  3. Do you need to build the entire dataset before you can calculate your statistics>

    Could you build (say) all of $data[1][Y][Z] for X=1; calculate the stats; and then discard that before building all $data[2][Y][Z] for X=2?

  4. What are you storing in each element of that 3d array?

    Is it just a number? If so, how big will that number get?

    If, for example, each element of the array held an integer < 255, the you can easily substitute a string for the 3 level arrays and save huge amounts of memory.

    Eg. This constructs a 100x100x100 3d array of small integers which requires 33MB of memory.

    @data = map[ map[ map int( rand 256), 0..99 ],0..99 ], 0..99;; print total_size \@data;; 33454784

    This on the other hand construct 100x100x100 2D array of strings. It contains the exact same information, but it only requires 1.6MB:

    @data = map[ map pack( 'C*', map int( rand 256), 0..99 ), 0..99 ], 0.. +99;; print total_size \@data;; 1614784

If you give us the information we ask for, we can almost certainly help you reduce your memory requirements.


With the rise and rise of 'Social' network sites: 'Computers are making people easier to use everyday'
Examine what is said, not who speaks -- Silence betokens consent -- Love the truth but pardon error.
"Science is about questioning the status quo. Questioning authority".
In the absence of evidence, opinion is indistinguishable from prejudice.


Comment on Re: Memory issue with cancer data (analogy)
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Re^2: Memory issue with cancer data (analogy)
by ZWcarp (Beadle) on Jul 25, 2013 at 20:17 UTC
    Sorry I know my description sucks I'll try to answer your questions by providing some of the actual data and the output which I made manually. There will never be set dimensions as ever dataset will change depending on the patients tumors coming in. The idea is to have a script that can handle any size dimensions.

    The file I need to read in is this structure. These 19 lines are taken from the real file which has 5,772,080 lines in the same format :

    Gene Name Patient ID Patient Diagnosis Ammino Acid Mutation a +nd Sit Protein Length AAK1 19679 adenocarcinoma L661I 21265 AAK1 19679 adenocarcinoma L664T 21265 AAK1 19679 adenocarcinoma L664T 21265 AAK1 19679 adenocarcinoma L664T 21265 AAK1 19679 adenocarcinoma L664T 21265 AAK1 19679 adenocarcinoma L664T 21265 AAK1 19676 adenocarcinoma L664T 21265 AAK1 19677 adenocarcinoma L64F 21265 AAK1 19678 adenocarcinoma L64R 21265 FKT1 101063 ER-PR-sitive_carcinoma p.L52R 2773 FKT1 103872 ER-PR-sitive_carcinoma p.E17K 2773 FKT1 107590 ER-PR-sitive_carcinoma p.E17K 2773 FKT1 107600 ER-PR-sitive_carcinoma p.E17K 2773 FKT1 1135911 NS E17K 2773 TET3 152 chronic_lymocytic_leukaemia p.R401H 10982 TET3 587220 adenocarcinoma M935V 10982 TET3 587220 adenocarcinoma R1534Q 10982 TET3 587256 adenocarcinoma G1356R 10982 TET3 587338 adenocarcinoma G1356W 10982
    Now I need to count all positions that match in Amino Acid Site (the number but not the letters of the 4th column) but are in different samples. Note : Patient ID19679 and AA mutation L664T only corresponds to a count of 2 because all of them are in the same patient except one in patient 19676.

    The out put needs to be in this format, where you have rows as genes and columns are 1-Length(the fifth column above). L is different for every gene. I've listed spans as no1.....no2 just for sake of space, but in the real file all these numbers in between have to be filled with 0's:

    1-Largest Gene Length AA site -1 AA site -2 AA site -3 4 +16 AA site -17 18..51etc AA site 52 AA site 64 654 +00 AA site 401 402.660 AA site 661 AA site 664 AA sit +e 935 AA site 1356 AA site 1534 AAK1 0 0 0 0 0 0 0 2 0 1 2 + 0 0 0 FKT1 0 0 0 0 4 0 1 0 0 0 0 + 0 0 0 TET3 0 0 0 0 0 0 0 0 1 0 0 + 1 2 1

    I'm simplifying because I also need to calculate a second table but this time with Amino acid position and mutation ( thus numbers and letters of Column 4) matching in different patients. Thats why my script is so elaborate, the $key3=$key4 is to remove the letters etc. I know i've done a poor job scripting it. Any advice would be fantastic!! Thanks so much for helping.

      See how you get on with this:

      #! perl -sw use strict; <>; #discard header line my %table; my %lengths; while( <> ) { my( $gene, $id, undef, $site, $len ) = split; my( $pos ) = $site =~ m[(\d+)]; ## extract the digits from t +he site undef $table{ $gene }{ $pos }{ $id }; ## adds the id as a key with + no value (saves space!) $lengths{ $gene } = $len; ## Save the gene lengths for + later } #print 'output header line here if required'; for my $gene ( sort keys %table ) { print "$gene"; my $p = 1; for my $pos ( sort{ $a <=> $b } keys %{ $table{ $gene } } ) { print "\t0" x ( $pos - $p ), "\t", scalar keys %{ $table{ $gen +e }{ $pos } }; $p = $pos + 1; } print "\t0" x ( $lengths{ $gene } - $p ), "\n"; }

      Invoke it as thisScript.pl < theInputFile > theOutputFile. It shouldn't take more than a minute or two to run.

      It'll probably need tweaking. Like adding an appropriate header line if that is a requirement. I couldn't work out what would be needed as all the output lines will be different lengths, as the genes are different lengths.


      With the rise and rise of 'Social' network sites: 'Computers are making people easier to use everyday'
      Examine what is said, not who speaks -- Silence betokens consent -- Love the truth but pardon error.
      "Science is about questioning the status quo. Questioning authority".
      In the absence of evidence, opinion is indistinguishable from prejudice.

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