1.
“BioMart is a query-oriented data management system developed jointly by the Ontario Institute for Cancer Research (OICR) and the European Bioinformatics Institute (EBI).”
Open Source – LGPL
* Perl API
→ Web Interface, Web Services Interface, REST API
* Java API
→ Mart Explorer GUI, MartShell
* 3rd Party Software
→ Bioclipse, biomaRt-BioConductor, Cytoscape, Galaxy, Taverna, WebLab
Databases in Biomart format:
Ensembl HapMap HTGT HGNC Dictybase Wormbase Gramene Europhenome UniPro Rat Genome Database DroSpeGe ArrayExpress DW Eurexpress GermOnLine PRIDE PepSeeker VectorBase
Pancreatic Expression Database Reactome EU Rat Mart Paramecium DB

2. A Mart is a collection of datasets (~=Database).
Marts are optimised for querying.
A Dataset has a main table, with an entry (and Primary Key) for each of the items of interest in that dataset (eg Mouse Transcripts).
Related bits of information about these items are hung off the table in dimension tables (eg. Affy Ids corresponding to this gene)‏
More Info:

3. Ensembl annotates everything at the transcript level:
AffyID
Ensembl_transcript_1
HUGO Symbol
Ensembl_transcript_2
Ensembl_transcript_3
1939_at ENST
1939_at ENST
1939_at ENST TP53
Affy Ids are mapped by Ensembl. If there is no clear match then that probe is not assigned to a gene.

4. Web Interface: http://www.biomart.org/biomart/martview/
Choose a Database (mart) to query (eg Ensembl)‏
Choose a Dataset from that mart to query (eg Mus Musculus Genes)‏

5. Filters
Use filters to select the members of the dataset in which you're interested
eg.
Limit to miRNA genes from Chr1 →

6. Attributes
Use attributes to define what bits of information you want to retrieve about the members of the dataset
eg. Gene ID, Transcript ID, Start, End and Status:

7. Results:

9. www.bioconductor.org source("http://bioconductor.org/biocLite.R")‏
“Bioconductor is an open source and open development software project
for the analysis and comprehension of genomic data.”
source("
#Default package set
biocLite()‏
#OR
biocLite(“someBiocPkg”)‏
biocLite(groupName=”pkgGroupName”)‏

10. Core Packages:
affy, affydata, affyPLM, annaffy, annotate, Biobase, Biostrings, DynDoc, gcrma, genefilter, geneplotter, hgu95av2.db, limma, marray, matchprobes, multtest, ROC, vsn, xtable, affyQCReport.
Alternative Package Groups
lite, affy, graph, all
Full Package Listing (software)‏
Full Package Listing (annotation)‏

11. Querying biomart from R:
# Install library
source(“
biocLite(“biomaRt”)‏
# Load library
library(biomaRt)‏
listMarts()‏
# result is just a data.frame, so you can subset it:
listMarts()[1:5,]
# or search it:
grep('ensembl', listMarts()[,1], value=TRUE)‏

12. mart <- useMart('ensembl', dataset='mmusculus_gene_ensembl')‏
# Select a mart
mart <- useMart('ensembl')‏
# List the available datasets (returns data.frame)‏
listDatasets(mart)‏
# Select a dataset
mart <- useDataset('mmusculus_gene_ensembl', mart=mart)‏
# Both in one:
mart <- useMart('ensembl', dataset='mmusculus_gene_ensembl')‏

13. # Available Filters (returns data.frame)‏ listFilters(mart)‏
# Available Attributes (returns data.frame)‏
listAttributes(mart)‏
# A Simple Query
getBM(filters=c('ensembl_gene_id'),
values=c('ENSMUSG ','ENSMUSG '),
attributes=c('ensembl_gene_id',
'ensembl_transcript_id',
'transcript_start',
'transcript_end'),
mart=mart)‏
ensembl_gene_id ensembl_transcript_id transcript_start transcript_end
1 ENSMUSG ENSMUST
2 ENSMUSG ENSMUST
3 ENSMUSG ENSMUST
4 ENSMUSG ENSMUST
5 ENSMUSG ENSMUST
6 ENSMUSG ENSMUST
7 ENSMUSG ENSMUST
8 ENSMUSG ENSMUST
9 ENSMUSG ENSMUST
10 ENSMUSG ENSMUST
11 ENSMUSG ENSMUST
12 ENSMUSG ENSMUST
13 ENSMUSG ENSMUST
14 ENSMUSG ENSMUST

14. # If using multiple filters, values should be a list
# If chromosome_name, start and end filters used they are auto
# interpreted as 'search within this region'
getBM(filters=c('chromosome_name',
'start',
'end' ),
values=list(10, , ),
attributes= c('ensembl_gene_id',
'start_position','end_position'),
mart=mart)‏
ensembl_gene_id start_position end_position
1 ENSMUSG
2 ENSMUSG
3 ENSMUSG
4 ENSMUSG

15. # Attributes and filters are organised into categories
# To get a list of the categories:
attributeSummary(mart)‏
filterSummary(mart)‏
# You can then list attributes and filters limited to a
# specified category:
listAttributes(mart, category='Variations')‏
# Filters can be either numeric, string or boolean.
# Boolean filters need a TRUE or FALSE value
# Determine type of filter with:
filterType('with_unigene', mart)‏

16. # Older versions of ensembl are archived, useful if you've
# got genome positions to a previous build
old.mart <- useMart('ensembl_mart_46',
dataset='mmusculus_gene_ensembl',
archive=TRUE)‏

17. Retrieving Sequences:
# can get complicated with getBM. Use the getSequence wrapper
# Genome Sequences always 5'-3' but...
# Web-Services mode (default): Strand is context dependant
# MySQL mode: Always top strand
#eg...
# BRCA1 peptide sequence from gene symbol
getSequence(id="BRCA1", type="mgi_symbol", seqType="peptide", mart = mart)‏
# REST transcript 20 bases upstream
getSequence(id='ENSMUST ', type='ensembl_transcript_id', seqType='transcript_flank', upstream=20, mart=mart)‏
# Chromosome 4 100,000, ,000,010
getSequence(chromosome=4, start= , end= , mart=mart, seqType="gene_exon", type="ensembl_gene_id")‏

18. seqTypes:
Note that any of the _flank types need an 'upstream' or 'downstream' argument to determine
the size of the flanking region. At the moment, you can't specify both.

19. Exporting Sequences:
# The exportFASTA function provides a quick way of saving
# sequences in FASTA format:
res <- getSequence(id="BRCA1", type="mgi_symbol", seqType="peptide", mart = mart)‏
exportFASTA(res, file='sequence.fa')‏
Ensembl mart deals with everything in terms of gene Ids, so getSequence doesn't let you just get arbitrary bits of sequence. It lets you get gene sequences, exon sequences, transcript sequences
If you're dealing in genome positions rather than gene Ids, have a look at the

20. Linking Datasets...
# Make mart connections for each of the datasets:
mouse.mart<-useMart('ensembl', dataset="mmusculus_gene_ensembl")‏
people.mart<-useMart('ensembl', dataset='hsapiens_gene_ensembl')‏
# In Ensembl, datasets are made of transcripts
# from a single species.
# Linking datasets amounts to homology
#eg. Get pos of mouse homolog to human 'TP53' gene
getLDS(attributes = c("hgnc_symbol","chromosome_name", "start_position"),
filters = "hgnc_symbol",
values = "TP53",
mart = people.mart,
attributesL = c("chromosome_name","start_position"),
martL = mouse.mart)‏ }
V1 V V3 V V5
1 TP
Ensembl mart deals with everything in terms of gene Ids, so getSequence doesn't let you just get arbitrary bits of sequence. It lets you get gene sequences, exon sequences, transcript sequences
If you're dealing in genome positions rather than gene Ids, have a look at the

21. Pretty HTML Output:
library(annotate)‏
# Provides the htmlpage function. Salient args are:
# genelist – a list or dataframe of IDs to be made into links
# filename
# title – for the table
# othernames – a list of other things to add to the table as is
# table.head – a character vector of col headers for the table.
# repository – a list of repositories to use for creating links
ids <- c('ENSMUSG ','ENSMUSG ')‏
genelist <- getBM(attributes=c('uniprot_swissprot_accession', 'entrezgene'), filters='ensembl_gene_id', values=ids, output='list', na.value=' ', mart=mart)‏
othernames <- getBM(attributes=c('ensembl_gene_id','mgi_symbol', 'description'), filters='ensembl_gene_id', values=ids, output='list', na.value='&nsbp;',mart=mart)‏
htmlpage(genelist=genelist, othernames=othernames, title='Some Genes', table.head=c('Uniprot', 'Entrezgene', 'Ensembl','Name', 'Description'), repository=list('sp', 'en'), filename='genes.html')‏
# Note that all the lists are expected to be in the right order
Ensembl mart deals with everything in terms of gene Ids, so getSequence doesn't let you just get arbitrary bits of sequence. It lets you get gene sequences, exon sequences, transcript sequences
If you're dealing in genome positions rather than gene Ids, have a look at the

23. More Info... Slides & examples:
Bioconductor Mailing List:
biomaRt Users' Guide:
vignette('biomaRt')‏
Biomart Website
Ensembl mart deals with everything in terms of gene Ids, so getSequence doesn't let you just get arbitrary bits of sequence. It lets you get gene sequences, exon sequences, transcript sequences
If you're dealing in genome positions rather than gene Ids, have a look at the
Slides & examples: