Bio::SAGE::Comparison README

#
# Copyright (c) 2004 Scott Zuyderduyn <scottz@bccrc.ca>.
# All rights reserved. This program is free software; you
# can redistribute it and/or modify it under the same
# terms as Perl itself.
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# $Id: README,v 1.1.1.1 2004/05/25 01:34:52 scottz Exp $
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BACKGROUND

Serial analysis of gene expression (SAGE) is a molecular 
technique for generating a near-global snapshot of a 
cell population’s transcriptome.  Briefly, the technique 
extracts short sequences at defined positions of 
transcribed mRNA.  These short sequences are then paired 
to form ditags.  The ditags are concatamerized to form 
long sequences that are then cloned.  The cloned DNA is 
then sequenced.  Bioinformatic techniques are then 
employed to determine the original short tag sequences, 
and to derive their progenitor mRNA.  The number of times
a particular tag is observed can be used to quantitate
the amount of a particular transcript.  The original 
technique was described by Velculescu et al. (1995) and 
utilized an ~14bp sequence tag.  A modified protocol 
was introduced by Saha et al. (2002) that produced ~21bp 
tags.

PURPOSE

This module facilitates the comparison of SAGE libraries.
Specifically:

  1. Calculations for determining the statistical
     significance of expression differences.
  2. Dynamically convert longer-tag libraries to
     a shorter type for comparison (e.g. comparing
     a LongSAGE vs. a regular SAGE library).

Both regular SAGE (14mer tag) and LongSAGE (21mer tag) 
are supported by this module.

Statistical significance in library comparisons is
calculated using the method described by Audic and 
Claverie (1997).  Code was generated by directly
porting the authors' original C source.

REFERENCES

  Velculescu V, Zhang L, Vogelstein B, Kinzler KW. (1995) 
  Serial analysis of gene expression. Science. 270:484-487.

  Saha S, Sparks AB, Rago C, Akmaev V, Wang CJ, Vogelstein B, 
  Kinzler KW, Velculescu V. (2002) Using the transcriptome 
  to annotate the genome. Nat. Biotechnol. 20:508-512.

  Audic S, Claverie JM. (1997) The significance of digital
  gene expression profiles. Genome Res. 7:986-995.