About SAGExplore

SAGExplore web server
    This server is a tool to assist the analysis and interpretation of results obtained by the technique Serial Analysis of Gene Expression (SAGE). The primary aim of the server is to facilitate the tag mapping process of SAGE. The secondary goal is to simplify tasks such as the analysis and interpretation of results, and to speed up the gene discovery process that is guided by those tags mapping into genomic regions currently classified as intergenic. The server has three independent modules, which are:
  1. Genome Explore: This module allows the user to browse and explore a genome, in terms of the context where potential or virtual SAGE tags are found for a given anchoring-tagging enzyme pair (a tutorial describing how to use this module is available here).
  2. Genome Mapping: This module allows the user to map his/her own experimental tags against the genome (tutorial).
  3. Library Mapping: This module allows the user to map his/her own experimental tags against the known SAGE libraries previously described in the literature (tutorial).
    The server uses a database of virtual genomic tags generated by a novel method for tag mapping in SAGE. The method is called Hierarchical Gene Assignment (HGA) and it is described in general terms below. A detailed explanation about how this method works has been already published (Malig et al., 2006).
Hierarchical Gene Assignment (HGA) method for tag mapping in SAGE
    The HGA method is a novel procedure for the tag mapping process in SAGE. It is based on using a full genomic sequence along with its current annotation (protein and RNA tables) for mapping the experimental SAGE tags. The HGA method assigns a confidence estimation to all those tags where two or more instances are observed in the genome (i.e. repeated tag sequences), thus allowing a reduction of ambiguity in the tag mapping process (or the ranking of ambiguous assignments by their individual confidences). The tag confidence assignments are derived from known experimental data. The HGA method provides an unambiguous prediction of which tag matches correspond to a real gene or to a region that currently is annotated as intergenic, thus facilitating the processes of discovering and characterizing new genes. For a detailed description of the method, read the following manuscript: Malig et al., 2006.
Features of the current release of SAGExplore server
The current version of SAGExplore server includes:
  • The full genome of Saccharomyces cerevisiae along with its existing genome annotation (release July 2005, obtained from the external SGD web site or also available here).
  • All potential NlaIII-BsmFI virtual tags in the genome are available.
  • TAG confidences estimated from the following experimental SAGE data: Velculescu et al. 1997, Kal et al. 1999 and Varela et al. 2005.
NOTE: Future releases of this server will incorporate the results of the HGA classification for other genomes, which include: Homo sapiens, Xenopus tropicalis, Mus musculus, Drosophila melanogaster and Arabidopsis thaliana. Furthermore, the incorporation of additional tags derived from the combination of different pairs of anchoring-tagging enzymes (e.g. long SAGE) for the existing genomes is also planned and it will be gradually added into this server.
  • Kal, A.J., van Zonneveld, A.J., Benes, V., van den Berg, M., Koerkamp, M.G., Albermann, K., Strack, N., Ruijter, J.M., Richter, A., Dujon, B., et al. (1999) Dynamics of gene expression revealed by comparison of serial analysis of gene expression transcript profiles from yeast grown on two different carbon sources. Mol. Biol. Cell 10, 1859-1872.
  • Malig, R., Varela, C., Agosin, E. and Melo, F. (2006) Accurate and unambiguous tag-to-gene mapping in SAGE by a hierarchical gene assignment procedure. BMC Bioinformatics 7, 487-508.
  • Norambuena, T., Malig, R. and Melo, F. (2007) SAGExplore: a web server for unambiguous tag mapping in serial analysis of gene expression oriented to gene discovery and annotation. Nucleic Acids Research (in press).
  • Varela, C., Cardenas, J., Melo, F. and Agosin, E. (2005) Quantitative analysis of wine yeast gene expression profiles under winemaking conditions. Yeast 22, 369-383.
  • Velculescu, V.E., Zhang, L., Zhou, W., Vogelstein, J., Basrai, M.A., Bassett Jr, D.E., Hieter, P., Vogelstein, B. and Kinzler, K.W. (1997) Characterization of the yeast transcriptome. Cell 88, 243-251.
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