Transcript Data Mining in Ensembl with BioMart

Data Mining in Ensembl with
BioMart
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Simple Text-based
Search Engine
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‘Mouse Gene’ Gives Us Results
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A More Complex Query is Not as
Useful
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BioMart- Data mining
• BioMart is a search engine that can
find multiple terms and put them into
a table format.
• Such as: human gene (IDs),
chromosome and base pair position
• No programming required!
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General or Specific Data-Tables
• All the genes for one species
• Or… only genes on one specific region of a
chromosome
• Or… genes on one region of a chromosome
associated with a disease
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BioMart Data Sets
• Ensembl genes
• Vega genes
• SNPs
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Markers
Phenotypes
Gene expression information
Gene ontology
Homology predictions
Protein annotation
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Web Interface
With BioMart, quickly extract gene-associated information from the
Ensembl databases.
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Information Flow
• Choose the species of interest (Dataset)
• Decide what you would like to know
about the genes (Attributes)
(sequences, IDs, description…)
• Decide on a smaller geneset using
Filters.
(enter IDs, choose a region …)
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Web Interface
Choose the
species of
interest
Choose what
information
to view.
Choose the gene
set using what
we know.
Three main stages: Dataset, Attributes and Filters.
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The First Step: Choose the Dataset
Homo sapiens
genes are the
default.
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The Second Step: Attributes
Four output
pages.
Attributes are what we want to know about the
genes.
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The SNP Attribute Page
Output variation information such as SNP
reference ID and alleles.
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Filters Allow Gene Selection
Choose the gene set by region, gene ID(s),
protein/domain type.
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Export Sequence or Tables
Genes and attributes are exported as sequence
(Fasta format) or tables.
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Query:
• For all mouse genes on chromosome
10 that are protein coding, I would like
to know the IDs in both Ensembl and
MGI.
• In the query:
Attributes: what we want to know.
Filters: what we know
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Query:
• For all mouse genes on chromosome
10 that are protein coding, I would like
to know the IDs in both Ensembl and
MGI.
• In the query:
Attributes: what we want to know.
Filters: what we know
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Query:
• For all mouse genes on chromosome
10 that are protein coding, I would like
to know the IDs in both Ensembl and
MGI.
• In the query:
Attributes: what we want to know.
Filters: what we know
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A Brief Example
Change dataset to
mouse
Mus musculus
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A Brief Example
Dataset has changed.
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Attributes (Output Options)
Click
Attributes.
Click on ‘GENE’.
Attributes allow us to choose what we wish to
know.
IDs are found in the ‘Features’ page.
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Attributes (Output Options)
Ensembl Gene ID is
selected
Default options selected:
Ensembl Gene ID and Transcript ID
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Attributes (Output Options)
‘Markersymbol ID’ will
give us the MGI ID
Scroll down to select MGI symbol.
Also select the accession number.
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The Results Table
‘Results’ give us Gene IDs for all mouse genes in
the Ensembl database.
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Select a Smaller Gene Set
Expand the
REGION panel
Select
‘Filters’
Instead of all mouse genes, select protein coding
genes on chromosome 10.
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Select Genes on Chromosome 10
Select
chromosome
10
Instead of all mouse genes, select protein coding
genes on chromosome 10.
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Select Protein Coding Genes
Gene type:
protein coding
Filters are set to chromosome 10 and
protein-coding genes. Genes must meet BOTH
criteria to be in the result table.
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Results (Preview)
For the full result
table: Go
This is a preview- if you are happy with the table,
click ‘Go’.
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Full Result Table
Ensembl Gene ID
Transcript
ID
MGI
symbol
MGI Accession
Number
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Original Query:
• For all mouse genes on chromosome
10 that are protein coding, I would like
to know the IDs in both Ensembl and
MGI.
• In the query:
Attributes: columns in the Result Table
Filters: what we know
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Other Export Options (Attributes)
• Sequences: UTRs, flanking sequences,
cDNA and peptides, etc
• Gene IDs from Ensembl and external
sources (MGI, Entrez, etc.)
• Microarray data
• Protein Functions/descriptions (Interpro,
GO)
• Orthologous gene sets
• SNP/ Variation Data
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Central Server
www.biomart.org
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WormBase
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HapMap
Population
frequencies
Interpopulation
comparisons
Gene
annotation
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DictyBase
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Uniprot, MSD
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GRAMENE
Rice, Maize, Arabidopsis genomes…
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How to Get There
• Either www.biomart.org/biomart/martview
• Or click on ‘BioMart’ from Ensembl
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Thanks
Arek Kasprzyk
Benoît Ballester
Syed Haider
Richard Holland
Damian Smedley