1. Data Mining with BioMart

2. Simple and … Complex Queries
Genes within a candidate region
Gene products with a particular protein domain …
Genomic location and description of all mouse and rat homologues of all human genes, that have transmembrane domains, are expressed in the cardiovascular system and are associated with non-synonymous SNPs

3. Ensembl Core Database Relational database Normalised
Each data point stored only once
Therefore:
Quick updates
Minimal storage requirements
But:
Many tables
Many joins for complicated queries
Slow for data mining applications

4. Normalised Schema gene_id gene_stable_id 9970 ENSG00000170365 1712
8240
ENSG
1967
ENSG …
gene_id
gene_symbol
9970
SMAD1
1712
SMAD2
8240
SMAD3
1967
SMAD4 …
gene_id
transcript_id
9970
ENST
1712
ENST
ENST
8240
ENST
1967
ENST …

5. BioMart Database Data warehouse De-normalised Query-optimised
Tables with apparent “redundancy”
Therefore:
Fast and flexible
Ideal for data mining
Produced from normalised core databases at every new release

6. De-Normalised Schema gene_stable_id transcript_id gene.symbol
ENSG
ENST
SMAD1
ENSG
ENST
SMAD2
ENST
ENSG
ENST
SMAD3
ENSG
ENST
SMAD4 …

7. BioMart
Developed jointly by the European Bioinformatics Institute (EBI) and Cold Spring Harbor Laboratory (CSHL)
Publicly available implementations at:
Ensembl
Central Server
Dictybase
Wormbase (WormMart)
Gramene (GrameneMart)
euGenes
HapMap (HapMart)
ZF-Models

8. BioMart

9. Data Sets Primary Ensembl Genes Vega Genes SNPs Secondary Markers
“Diseases”
Gene ontology
Gene expression information
Homology predictions
Protein annotation

10. Information Flow START FILTER OUTPUT DATABASE SPECIES REGION SNP
PROTEIN
HOMOLOGY
GENE
EXPRESSION
RefSeq
InterPro GO
Swiss-Prot
EMBL
Affymetrix
FILTER
FASTA
FILE
EXCEL
TEXT
GTF
HTML
OUTPUT
REGION
SNP
PROTEIN
HOMOLOGY
GENE
EXPRESSION

11. BioMart Example
Find all Ensembl genes on the short arm of human chromosome 1 which are known to be associated with a disease
Export the 100 bp upstream of the transcripts of the above genes

12. 2. Select “Homo sapiens genes (NCBI36)”
1. Select “Ensembl 38”
3. Click “next”
2. Select “Homo sapiens genes (NCBI36)”

13. 5. Select “Band Start p36.33 – End p11.1”
4. Select “Chromosome 1”
7. Click “next”
5. Select “Band Start p36.33 – End p11.1”
6. Select “with Disease Association Only”

14. 8. Select Attribute Page “Features” Summary of actions
9. Select “Ensembl Gene ID” and “Ensembl Transcript ID”

15. 10. Select “Disease OMIM ID” and “Disease description”
11. Select Output format “MS Excel”
12. Click “export”

17. 13. Select Attribute Page “Sequences”
17. Click “export”
14. Select “Flank (Transcript)”
15. Enter “Upstream flank 100”
16. Select Header information

19. There are other ways… MartShell
Command line interface to Mart written in Java
Mart Query Language

20. What about queries not possible to do in BioMart?
MySQL queries on ensembldb.ensembl.org
MySQL client
Perl API
BioPerl and Ensembl modules
Java API

21. Q
& A
Q U E S T I O N S
A N S W E R S

22. Exercises
«The range and complexity of the questions you can address through the Ensembl MartView resource is truly impressive. We really encourage you to spend some time playing with it …»