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Bioinformatics Advance Access originally published online on February 3, 2007
Bioinformatics 2007 23(7):903-905; 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 1,2,*, Jeff Trimarchi 3, Constance L. Cepko 3,4, Sandro J. de Souza 2, Lucila Ohno-Machado 5,6 and Winston P. Kuo 5,7,8

1Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, 2Laboratory of Computational Biology, Ludwig Institute for Cancer Research, São Paulo Branch, Brazil, 3Department of Genetics, Harvard Medical School, 4Howard Hughes Medical Institute, Harvard Medical School, 5Decision Systems Group, Brigham and Women's Hospital, 6Division of Health Sciences and Technology, Harvard Medical School and MIT, Boston, 7Department of Organismic and Evolutionary Biology/FAS, Harvard University, and 8Department of Developmental Biology, Harvard School of Dental Medicine, Harvard University, Cambridge, MA, USA

*To whom correspondence should be addressed.


  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 datasets. ACTG can annotate SAGE (14 or 21 bp), MPSS (17 or 20 bp) and SBS (16 bp) data for both human and mouse organisms.

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

Contact: pgalante{at}ludwig.org.br

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: John Quackenbush

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

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