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Top Forums Shell Programming and Scripting Create combinations based on scores Post 302958958 by jianp83 on Tuesday 27th of October 2015 03:05:51 PM
Old 10-27-2015
Hi RudiC, thank you, will this help deal with the 345 million records in the score table problem? Is there a way we can avoid the 3 for loops? Thanks a lot for your help.
 

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Bio::SearchDist(3pm)					User Contributed Perl Documentation				      Bio::SearchDist(3pm)

NAME
Bio::SearchDist - A perl wrapper around Sean Eddy's histogram object SYNOPSIS
$dis = Bio::SearchDist->new(); foreach $score ( @scores ) { $dis->add_score($score); } if( $dis->fit_evd() ) { foreach $score ( @scores ) { $evalue = $dis->evalue($score); print "Score $score had an evalue of $evalue "; } } else { warn("Could not fit histogram to an EVD!"); } DESCRIPTION
The Bio::SearchDist object is a wrapper around Sean Eddy's excellent histogram object. The histogram object can bascially take in a number of scores which are sensibly distributed somewhere around 0 that come from a supposed Extreme Value Distribution. Having add all the scores from a database search via the add_score method you can then fit a extreme value distribution using fit_evd(). Once fitted you can then get out the evalue for each score (or a new score) using evalue($score). The fitting procedure is better described in Sean Eddy's own code (available from http://hmmer.janelia.org/, or in the histogram.h header file in Compile/SW). Bascially it fits a EVD via a maximum likelhood method with pruning of the top end of the distribution so that real positives are discarded in the fitting procedure. This comes from an orginally idea of Richard Mott's and the likelhood fitting is from a book by Lawless [should ref here]. The object relies on the fact that the scores are sensibly distributed around about 0 and that integer bins are sensible for the histogram. Scores based on bits are often ideal for this (bits based scoring mechanisms is what this histogram object was originally designed for). CONTACT
The original code this was based on comes from the histogram module as part of the HMMer2 package. Look at http://hmmer.janelia.org/ Its use in Bioperl is via the Compiled XS extension which is cared for by Ewan Birney (birney@ebi.ac.uk). Please contact Ewan first about the use of this module FEEDBACK
Mailing Lists User feedback is an integral part of the evolution of this and other Bioperl modules. Send your comments and suggestions preferably to one of the Bioperl mailing lists. Your participation is much appreciated. bioperl-l@bioperl.org - General discussion http://bioperl.org/wiki/Mailing_lists - About the mailing lists Support Please direct usage questions or support issues to the mailing list: bioperl-l@bioperl.org rather than to the module maintainer directly. Many experienced and reponsive experts will be able look at the problem and quickly address it. Please include a thorough description of the problem with code and data examples if at all possible. Reporting Bugs Report bugs to the Bioperl bug tracking system to help us keep track the bugs and their resolution. Bug reports can be submitted via the web: https://redmine.open-bio.org/projects/bioperl/ APPENDIX
The rest of the documentation details each of the object methods. Internal methods are usually preceded with a _ add_score Title : add_score Usage : $dis->add_score(300); Function: Adds a single score to the distribution Returns : nothing Args : fit_evd Title : fit_evd Usage : $dis->fit_evd(); Function: fits an evd to the current distribution Returns : 1 if it fits successfully, 0 if not Args : fit_Gaussian Title : fit_Gaussian Usage : Function: Example : Returns : Args : evalue Title : evalue Usage : $eval = $dis->evalue($score) Function: Returns the evalue of this score Returns : float Args : _engine Title : _engine Usage : $obj->_engine($newval) Function: underlyine bp_sw:: histogram engine Returns : value of _engine Args : newvalue (optional) perl v5.14.2 2012-03-02 Bio::SearchDist(3pm)
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