Data Mining in Ensembl with EnsMart

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Data Mining in Ensembl with EnsMart
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Possible queries

• All genes from a candidate region
• Genes with a particular protein domain
• Members of a protein family
• Genes associated with SNPs

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Specific queries

• Disease related genes between markers D10S255 and
  D10S259
• Transmembrane proteins with an Ig-MHC domain
  (IPR003006) on chromosome 2
• Genes with associated coding SNPs on chromosomal
  band 5q35.3
• Mouse homologues for human disease genes.

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More specific queries

• Human genes with upstream regions conserved
  w.r.t. mouse
• Upstream sequence for all Ensembl genes mapped to
  U95A chip (similarly, complete genomic annotation
  of MG_U74).
• Genomic location and description of all mouse,
  rat and fugu homologues of all human genes, with
  transmembrane domains, expressed in
  cardiovascular system and have non-synonymous
  SNPs.

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EnsMart vertical and horizontal data integration
Ensembl Genes
SNPs
EST Genes
Vega Genes
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Ensembl data sets
Genes EST Markers Diseases Protein
Annotation SNPs Homology Expression
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EnsMart

• Data retrieval tool
• Query builder interface
• Gene or SNP lists
• Associated features or sequences
• Various output formats

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Information flow
start
filter
output
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Species and focus
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Restrict your query
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Restrict your query
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Select output options
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Select output options
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Output formats
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Obtaining sequences
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Ensembl core database

• Normalised
• Each data point stored only once
• Quick updates
• Minimal storage requirements
• But
• Many tables
• Many joins for complicated queries
• Slow for data mining questions

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Mart database

• De-normalised
• Tables with redundant information
• Query-optimised
• Fast and flexible
• Ideal for data mining

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Acknowledgements

• Mart database
• Arek Kasprzyk
• Damian Keefe
• Damian Smedley
• Darin London
• Craig Meslopp
• User interface (MartView)
• Will Spooner
• Data and general support
• The entire Ensembl team