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MatchMiner: a tool for batch navigation among gene and gene product identifiers.

Bussey KJ, Kane D, Sunshine M, Narasimhan S, Nishizuka S, Reinhold WC, Zeeberg B, Ajay W, Weinstein JN - Genome Biol. (2003)

Bottom Line: MatchMiner is a freely available program package for batch navigation among gene and gene product identifier types commonly encountered in microarray studies and other forms of 'omic' research.The user inputs a list of gene identifiers and then uses the Merge function to find the overlap with a second list of identifiers of either the same or a different type or uses the LookUp function to find corresponding identifiers.

View Article: PubMed Central - HTML - PubMed

Affiliation: Genomics and Bioinformatics Group, Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, NIH Building 37, Bethesda, MD 20892-4255, USA.

ABSTRACT
MatchMiner is a freely available program package for batch navigation among gene and gene product identifier types commonly encountered in microarray studies and other forms of 'omic' research. The user inputs a list of gene identifiers and then uses the Merge function to find the overlap with a second list of identifiers of either the same or a different type or uses the LookUp function to find corresponding identifiers.

Show MeSH
Database relational table schema for MatchMiner. (a) Logical database representation. Data are incorporated from the UCSC Human Genome Build, LocusLink, UniGene, OMIM, and the Affymetrix annotation sets for HU95 and HU133 chips. Each candidate gene is assigned a gene index in the GeneIdx table. These gene indexes are used as keys for all of the MatchMiner operations. The number of many-to-many relationships in the model illustrates the complexity of the data. (b) Physical representation of the database. The implementation currently includes 14 tables with about 12 million rows.
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Figure 2: Database relational table schema for MatchMiner. (a) Logical database representation. Data are incorporated from the UCSC Human Genome Build, LocusLink, UniGene, OMIM, and the Affymetrix annotation sets for HU95 and HU133 chips. Each candidate gene is assigned a gene index in the GeneIdx table. These gene indexes are used as keys for all of the MatchMiner operations. The number of many-to-many relationships in the model illustrates the complexity of the data. (b) Physical representation of the database. The implementation currently includes 14 tables with about 12 million rows.

Mentions: As shown schematically in Figures 1 and 2, MatchMiner leverages information from the four public databases listed above, and from Affymetrix, by parsing them into relational tables for use in doing translations. The LookUp function can operate interactively on single identifiers or in batch mode on a list of identifiers in a file. When used interactively for one or a few genes, it saves the user the trouble of querying five different databases and collating the data. More important, however, is batch querying of a list file, for instance a list of the dozens or hundreds or thousands of genes that show interesting differences between samples in a microarray experiment. In this mode, the user specifies the input and output identifier types, as well as the search algorithms to be used in traversing the various data sources (Table 1). The program is context-sensitive in that it will search only the pertinent data sources (for example, only UniGene to identify IMAGE clone ids, which are not found in the other sources). An important feature is the optional output of diagnostic metadata that tell the user in which source (s) the identifier was found and whether an input identifier corresponds to more than one gene. This feature enables the user to judge the reliability of matches. The results can be displayed in HTML format or downloaded as tab-delimited text suitable for direct entry into a spreadsheet program. A summary indicates the number of successful and unsuccessful translations.


MatchMiner: a tool for batch navigation among gene and gene product identifiers.

Bussey KJ, Kane D, Sunshine M, Narasimhan S, Nishizuka S, Reinhold WC, Zeeberg B, Ajay W, Weinstein JN - Genome Biol. (2003)

Database relational table schema for MatchMiner. (a) Logical database representation. Data are incorporated from the UCSC Human Genome Build, LocusLink, UniGene, OMIM, and the Affymetrix annotation sets for HU95 and HU133 chips. Each candidate gene is assigned a gene index in the GeneIdx table. These gene indexes are used as keys for all of the MatchMiner operations. The number of many-to-many relationships in the model illustrates the complexity of the data. (b) Physical representation of the database. The implementation currently includes 14 tables with about 12 million rows.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC154578&req=5

Figure 2: Database relational table schema for MatchMiner. (a) Logical database representation. Data are incorporated from the UCSC Human Genome Build, LocusLink, UniGene, OMIM, and the Affymetrix annotation sets for HU95 and HU133 chips. Each candidate gene is assigned a gene index in the GeneIdx table. These gene indexes are used as keys for all of the MatchMiner operations. The number of many-to-many relationships in the model illustrates the complexity of the data. (b) Physical representation of the database. The implementation currently includes 14 tables with about 12 million rows.
Mentions: As shown schematically in Figures 1 and 2, MatchMiner leverages information from the four public databases listed above, and from Affymetrix, by parsing them into relational tables for use in doing translations. The LookUp function can operate interactively on single identifiers or in batch mode on a list of identifiers in a file. When used interactively for one or a few genes, it saves the user the trouble of querying five different databases and collating the data. More important, however, is batch querying of a list file, for instance a list of the dozens or hundreds or thousands of genes that show interesting differences between samples in a microarray experiment. In this mode, the user specifies the input and output identifier types, as well as the search algorithms to be used in traversing the various data sources (Table 1). The program is context-sensitive in that it will search only the pertinent data sources (for example, only UniGene to identify IMAGE clone ids, which are not found in the other sources). An important feature is the optional output of diagnostic metadata that tell the user in which source (s) the identifier was found and whether an input identifier corresponds to more than one gene. This feature enables the user to judge the reliability of matches. The results can be displayed in HTML format or downloaded as tab-delimited text suitable for direct entry into a spreadsheet program. A summary indicates the number of successful and unsuccessful translations.

Bottom Line: MatchMiner is a freely available program package for batch navigation among gene and gene product identifier types commonly encountered in microarray studies and other forms of 'omic' research.The user inputs a list of gene identifiers and then uses the Merge function to find the overlap with a second list of identifiers of either the same or a different type or uses the LookUp function to find corresponding identifiers.

View Article: PubMed Central - HTML - PubMed

Affiliation: Genomics and Bioinformatics Group, Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, NIH Building 37, Bethesda, MD 20892-4255, USA.

ABSTRACT
MatchMiner is a freely available program package for batch navigation among gene and gene product identifier types commonly encountered in microarray studies and other forms of 'omic' research. The user inputs a list of gene identifiers and then uses the Merge function to find the overlap with a second list of identifiers of either the same or a different type or uses the LookUp function to find corresponding identifiers.

Show MeSH