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Bioinformatics Advance Access published online on February 3, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm023
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© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Automatic Correspondence of Tags and Genes (ACTG): A Tool for the Analysis of SAGE, MPSS, and SBS Data

Pedro A. F. Galante a,b,*, Jeff Trimarchi c, Constance L. Cepko c,d, Sandro J. de Souza b, Lucila Ohno-Machado e,f and Winston P. Kuo e,g

a Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil
b Laboratory of Computational Biology, Ludwig Institute for Cancer Research, São Paulo Branch
c Department of Genetics, Harvard Medical School
dHoward Hughes Medical Institute, Harvard Medical School
e Decision Systems Group, Brigham and Women’s Hospital
f Division of Health Sciences and Technology, Harvard Medical School and MIT
g Department of Organismic and Evolutionary Biology/FAS, Harvard University

*To whom correspondence should be addressed. Pedro Galante, E-mail: pgalante{at}ludwig.org.br


  Abstract

Summary: A critical step in any SAGE, MPSS, and SBS data analysis is tag-to-gene assignment. Current available tools are limited by a tag-by-tag annotation process and/or do not provide the dataset that is used to produce a complete tag-to-gene mapping. We developed ACTG, a web-based application that allows a large-scale tag-to-gene mapping using several reference data sets. ACTG can annotate SAGE (14 bps or 21 bps), MPSS (17 bps or 20 bps), and SBS (16 bp) data for both human and mouse genomesorganisms.

Availability: http://retina.med.harvard.edu/ACTG/

Associate Editor: John Quackenbush

Received on October 23, 2006; revised on December 22, 2006; accepted on January 19, 2007

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