Download Online resources for genetic variation study-Part One

Online Resources for
Genetic Variation Study – Part One
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Online Resources for
Genetic Variation Study – Part One
Yi-Bu Chen, Ph.D.
Bioinformatics Specialist
Norris Medical Library
University of Southern California
323-442-3309
[email protected]
Dec. 6, 2007
Workshop Outline
 Overview of Bioinformatics Support Program at NML
 Human Genetic Variation Overview
Main types of genetic variations
Basics of the single nucleotide polymorphisms (SNPs)
 NCBI Genetic Variation Resources: dbSNP and OMIM
dbSNP overview
dbSNP search examples
OMIM overview
 International HapMap Project
The HapMap project: overview and major findings
HapMap search examples




The Perlegen Genetic Variation Database
Genome Variation Server (SeattleSNPs)
Ensembl SNPs
Hands-on Search Question
Polymorphisms: How different are we?
Human vs. Chimp
Human vs. Human
~96% overall (~99% similar in
terms of SNPs)
~99.9% similar with around 3.2 million
single nucleotide differences (account for
up to 90% of all genomic variations, total
possible SNPs near 12 millions)
Adapted from a lecture slide by Jonathan Wren, NYU
Why do we care about genetic variations?
1. Genetic variations underlie
phenotypic differences among
different individuals
2. Genetic variations determine our
predisposition to complex diseases and responses
to drugs and environmental factors
3. Genetic variations reveal
clues of ancestral human
migration history
Main Types of Genetic Variations
A. Single nucleotide mutation
 Resulting in single nucleotide polymorphisms (SNPs)
 Accounts for up to 90% of human genetic variations
 Majority of SNPs do NOT directly or significantly contribute to any phenotypes
B. Insertion or deletion of one or more nucleotide(s)
1. Tandem repeat polymorphisms
 Tandem repeats are genomic regions consisting of variable length of sequence
motifs repeating in tandem with variable copy number.
 Used as genetic markers for DNA finger printing (forensic, parentage testing)
 Many cause genetic diseases
 Microsatelites (Short Tandem Repeats): repeat unit 1-6 bases long
 Minisatelites: repeat unit 11-100 bases long
2. Insertion/Deletion (INDEL or DIPS) polymorphisms
Often resulted from localized rearrangements between homologous tandem
repeats.
C. Gross chromosomal aberration
 Deletions, inversions, or translocation of large DNA fragments
 Rare but often causing serious genetic diseases
How many variations are present
in human genome?
 SNPs appear once per 0.1-1 kb interval or on average 1
per 300 bp. Considering the size of entire human
genome (3.2 x109 bp), the total number of SNPs is well
above 11 million. The high density and relatively easier
assay make SNPs the ideal genomic markers.
 In sillico estimation of potentially polymorphic variable
number tandem repeats (VNTR) are over 100,000
across the human genome
 The short insertion/deletions are very difficult to
quantify and the number is likely to fall in between
SNPs and VNTR.
Types of Single Base Substitutions
 Transitions
Change of one purine (A,G) for another purine, or a
pyrimidine (C,T) for another pyrimidine
 Transversions
Change of a purine (A,G) for a pyrimidine (C,T), or
vice versa.
 The cytosine to thymine (C>T) transition accounts
for approximately 2 out of every 3 SNPs in human
genome.
SNP or Mutation?
 Call it a SNP IF
the single base change occurs in a population at a
frequency of 1% or higher.
 Call it a mutation IF
the single base change occurs in less than 1% of a
population.
 A SNP is a polymorphic position where the point
mutation has been fixed in the population.
From a Mutation to a SNP
SNPs Classification
SNPs can occur anywhere on a genome, they are classified based on their locations.
 Intergenic region
 Gene region
can be further classified as promoter region, and coding region
(intronic, exonic, promoter region, UTR, etc.)
Coding Region SNPs
 Missense – amino acid change
 Nonsense – changes amino acid to stop codon.
Geospiza Green Arrow™ tutorial by Sandra Porter, Ph.D.
 Synonymous
 Non-Synonymous
The Consequences of SNPs
The phenotypic consequence of a SNP is
significantly affected by the location where it
occurs, as well as the nature of the mutation.
 No consequence
 Affect gene transcription quantitatively or
qualitatively.
 Affect gene translation quantitatively or
qualitatively.
 Change protein structure and functions.
 Change gene regulation at different steps.
Simple/Complex Genetic Diseases and SNPs
 Simple genetic diseases (Mendelian diseases) are
often caused by mutations in a single gene.
-- e.g. Huntington’s, Cystic fibrosis, PKU, etc.
 Many complex diseases are the result of mutations
in multiple genes, the interactions among them as
well as between the environmental factors.
-- e.g. cancers, heart diseases, Alzheimer's, diabetes,
asthmas, etc.
 Majority of SNPS may not directly cause any
diseases.
 SNPs are ideal genomic markers (dense and easy to
assay) for locating disease loci in association studies.
Main Genetic Variation Resources
 NCBI dbSNP
http://www.ncbi.nlm.nih.gov/SNP/index.html
 NCBI Online Mendelian Inheritance in Man
(OMIM)
http://www.ncbi.nlm.nih.gov/sites/entrez?db=OMIM
 International HapMap Project
http://www.hapmap.org/
 Perlegen
http://genome.perlegen.com
 Genome Variation Server (Seattle SNPs)
http://gvs.gs.washington.edu/GVS/
Where to Find Bioinformatics Resources for
Genetic Variation Studies?
 OBRC: Online Bioinformatics
Resources Collection (Univ. of Pittsburgh)
http://www.hsls.pitt.edu/guides/genetics/obrc
The most comprehensive annotated bioinformatics
databases and software tools collection on the Web, with
over 200 resources relevant to genetic variation studies.
 HUGO Mutation Database Initiative
http://www.hgvs.org/dblist/dblist.html
NCBI dbSNP Database: Overview
 URL: http://www.ncbi.nlm.nih.gov/SNP/index.html
 The NCBI’s Single Nucleotide Polymorphism
database (dbSNP) is the largest and primary
public-domain archive for simple genetic variation
data.
 The polymorphisms data in dbSNP includes:
 Single-base nucleotide substitutions (SNPs)
 Small-scale multi-base deletions or insertions variations
(also called deletion insertion polymorphisms or DIPs or
INDELs)
 Microsatellite tandem repeat variations (also called short
tandem repeats or STRs).
dbSNP Data Stats (build 128, Oct, 2007)
http://www.ncbi.nlm.nih.gov/SNP/snp_summary.cgi
dbSNP Data Types
The dbSNP contains two classes of records:
 Submitted record
The original observations of sequence
variation; submitted SNPs (SS) records
started with ss (ss5586300)
 Computationally annotated record
Generated during the dbSNP "build" cycle by
computation based the original submitted
data, Reference SNP Clusters (ref SNP) start
with rs (rs4986582)
dbSNP Submitted Record
 Provides information on the SNP and conditions under
which it was collected.
 Provides links to collection methods (assay technique),
submitter information (contact data, individual submitter),
and variation data (frequencies, genotypes).
ss5586300
From Submitted Record to Reference SNP Cluster
SNPs records submitted
by researchers
SNP position mapped
to the reference genomic
contigs
If the SNP position not unique, it will be
assigned to the existing RefSNP cluster
If the SNP position is
unique, a new RS# is
assigned
Different Ways to Search SNPs in dbSNP
 dbSNP Web site
http://www.ncbi.nlm.nih.gov/SNP/index.html
Direct search of SS record; batch search; allow SNP record
submission; NO search limits
 Entrez SNP
http://www.ncbi.nlm.nih.gov/sites/entrez?db=Snp
Search limits options allows precise retrieval
 Entrez Gene Record’s SNP Links Out Feature
Direct links to corresponding SNP records; access to genotype
and linkage disequilibrium data
 NCBI’s MapViewer
Visualize SNPs in the genomic context along with other types
of genetic data.
Search SNPs from dbSNP Web Page
 dbSNP Web site
http://www.ncbi.nlm.nih.gov/SNP/index.html
Search SNPs from Entrez SNP Web Page
 Entrez SNP
http://www.ncbi.nlm.nih.gov/sites/entrez?db=Snp
The dbSNP is a part of the Entrez integrated information
retrieval system and may be searched using either qualifiers
(aliases) or a combination search limits from 14 different
categories.
Entrez SNP Search Limits
 Organisms
 Chromosome (including W and Z for non-mammals)
 Chromosome Ranges
 Map Weight (how many times in genome)
 Function Class (coding non-synonymous; intron; etc.)
 SNP Class (types of variations)
 Method Class (methods for determining the variations)
 Validation Status (if and how the data is validated)
 Variation Alleles (using IUPAC- codes)
 Annotation (Records with links to other NCBI database)
 Heterozygosity (% of heterozygous genotype)
 Success Rate (likelihood that the SNP is real)
 Created Build ID
 Updated Build ID
http://www.ncbi.nlm.nih.gov/portal/query.fcgi?db=Snp
http://www.ensembl.org/common/helpview?kw=snpview;ref=
Search dbSNP: Example 1
Some mutations on human BRCA1 gene
have been reported to be involved in the
early onset of breast cancer.
Retrieve all validated non-synonymous
coding reference SNPs for BRCA1 from
dbSNP.
Hint: starting from the Entrez SNP: http://www.ncbi.nlm.nih.gov/sites/entrez?db=Snp
Entrez SNP Search Results Example 1
dbSNP Ref SNP Record Example 1: Summery
http://www.ncbi.nlm.nih.gov/SNP/snp_ref.cgi?rs=4986852
This Ref SNP cluster
contains multiple
submitted SNP records
from different groups
dbSNP Ref SNP Record Example 1:
SNP position and the flank region
dbSNP Ref SNP Record Example 1:
GeneView of an individual SNP
Because of alternative splicing, the very same SNP
can locate in different region of the transcripts.
dbSNP Ref SNP Record Example 1:
TableView of an individual SNP
Notice that the individual
SNP is mapped to the
same position on the
reference genomic contig,
but different positions on
mRNAs and proteins due
to alternative splicing.
dbSNP Ref SNP Record Example 1:
Links to Various Annotated NCBI Databases
Link to the
OMIM record
where
documented
clinical and
genetic data of
this SNP can
be found.
Warning: the lack of OMIM link does not necessary mean
that this SNP is unrelated to any OMIM record.
dbSNP Ref SNP Record Example 1:
Population Allele Frequency, Genotype and Heterozygosity Data
Link to the detailed
population genotype
data.
Data from National
Cancer Institute.
Data from The NIH
Polymorphism
Discovery Resource
Data from Centre
d'Etude du
Polymorphisme
Human (CEPH).
Data from the
International
HapMap Project.
dbSNP Ref SNP Record Example 1: GeneVeiw and SequenceView of ALL SNPs
dbSNP Ref SNP Record Example 1:
Links to View SNPs on 3D Structure, Conserved Domains,
and Multiple Sequence Alignment
Search dbSNP: Example 2
Mutations in Dopamine Receptor 5 (DRD5)
gene have been observed in patients with
various neurological disorders.
Find how many refSNP records have been
reported for DRD5. Show all refSNPs in
the context of a chromosome.
Hint: starting from the Entrez Gene: http://www.ncbi.nlm.nih.gov/sites/entrez?db=gene
Search dbSNP: SNP Links from Entrez Gene Record
Search dbSNP: SNP Display Using NCBI Map Viewer
Search dbSNP: Configure Map Viewer
to Display other Relevant Data
SNPs Display in Map Viewer: Legend
Click on any
column headings
to see the refSNPs
legend.
http://www.ncbi.nlm.nih.gov/SNP/get_html.cgi?whichHtml=verbose
SNPs Display in Map Viewer: Legend
Online Mendelian Inheritance in Man (OMIM):
A Brief Overview
 URL: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=OMIM
 OMIM is a human genetic disorders database built and curated using
results from published studies.
 Each OMIM record provides a summary of the current state of knowledge
of the genetic basis of a disorder, which contains the following information:
 description and clinical features of a disorder or a gene involved in
genetic disorders;
 biochemical and other features;
 cytogenetics and mapping;
 molecular and population genetics;
 diagnosis and clinical management;
 animal models for the disorder;
 allelic variants.
 OMIM is searchable via NCBI Entrez, and its records are cross-linked to
other NCBI resources.
Online Mendelian Inheritance in Man Stats
•http://www.ncbi.nlm.nih.gov/Omim/mimstats.html
OMIM: Allelic Variants
 The OMIM database includes genetic disorders caused by
various mutation/variation, from SNPs to large-scale
chromosomal abnormalities.
 The listed allelic variants are searchable through the "Allelic
Variants" field.
 Single nucleotide substitutions (SNPs);
 small insertions and deletions (INDEL/DIPS);
 frame shifts caused by these INDELs.
 Allelic variants are represented by a 10-digit OMIM number,
and can be searched in two ways:
 Search for a gene or a disease, when retrieved, view its allelic
variants.
 Use the Limits to narrow your search to:
-- retrieve only records that contain allelic variant information;
-- search for particular terms within the allelic variants field.
Notes on OMIM Allelic Variants
For most genes, only selected mutations are included
Criteria for inclusion include: the first mutation to be
discovered, high population frequency, distinctive phenotype,
historic significance, unusual mechanism of mutation, unusual
pathogenetic mechanism, and distinctive inheritance.
Most of the allelic variants represent diseaseproducing mutations, NOT polymorphisms.
A few polymorphisms are included, many of which
show a positive statistical correlation with particular
common disorders.
Few neutral polymorphisms are included in OMIM.
Some SNPs in the dbSNP records are not linked to the
corresponding OMIM records.
http://www.ncbi.nlm.nih.gov/entrez/dispomim.cgi?id=113705
Sequence variations view in UniProt Beta
http://beta.uniprot.org/uniprot/P38398
Assessing Polymorphisms: Genotypes and Genotyping
Genotype: Each person has two copies of all
chromosomes except the sex chromosomes. The set of
alleles at a given locus forms the genotype.
Genotyping: the process of identifying what genotype a
person has for any given locus (loci).
Whole-genome genotyping of all SNPs in a human
genome? (11.8 million and counting)
Technologically daunting
Prohibitively expensive and time consuming
Assessing Polymorphisms: the Origin of Haplotype
 Two ancestral chromosomes scrambled
through recombination over many
generations to yield different descendant
chromosomes.
 If a genetic variant marked by the X on
the ancestral chromosome increases the
risk of a particular disease, the two
descendants who inherit that part of the
ancestral chromosome will be at
increased risk.
 Adjacent to the variant marked by the X
are many SNPs that can be used to
identify the location of the variant.
 Haplotype: A particular combination of
alleles along a chromosome that tends to
be inherited as a unit.
http://www.hapmap.org/originhaplotype.html
Adapted from Nature 426, 6968: 789-796 (2003)
Assessing Polymorphisms:
Linkage Disequilibrium, Haplotype Block, and Tag SNPs
 Linkage Disequilibrium (LD): If two alleles tend to be inherited together more often
than would be predicted, then the alleles are in linkage disequilibrium.
 If most SNPs have highly significant correlation to one or more of neighbors, these
correlations can be used to generate haplotypes, which represent excellent proxies
for individual SNP.
 Because haplotypes may be identified by a much small number of SNPs (tag SNPs),
assessing polymorphisms via haplotypes dramatically reduces genotyping work.
Assessing Polymorphisms: Tag SNPs
 Tag SNP: a representative SNP enabling to infer (or predict)
other SNPs of its “neighborhood” (both distance and
genealogically wise).
 An r2 of 0.8 or greater is sufficient for tag SNP mapping to
obtain a good coverage of untyped SNPs.
 Tag SNPs allow genotyping of a lower number of marker SNPs
with very small losses in power.
 If LD between SNPs is low, almost every SNP might have to be
genotyped to get all variation information.
51
Goals
 Create a public genome-wide
database of common human genetic
variation in the context of geographic
distribution
 Provide such information to guide
genetic studies of clinical phenotypes
 Phase I (Oct. 2002)
 One million common SNPs (every 5 kb across the genome) were
genotyped in 269 DNA samples from four populations.
 Common SNPs : Minor Allele Frequency ≥ 0.05
 YRI : Yoruba in Nigeria (30 trios), CEU : Utah with European
ancestry (30 trios), CHB : 45 Han Chinese, JPT: 44 Japanese
 Phase II
 An additional 4.6 million SNPs are genotyped.
 ENCODE (Encyclopedia of DNA Elements)
 Collection of ten regions, each 500kb in length.
 Each 500 kb region was re-sequenced and all SNPs were genotyped.
HapMap Progress
PHASE I – completed
 1,000,000 SNPs successfully typed in all 269 HapMap samples
 At least one common SNP every 5 kb across the genome
 ENCODE variation reference resource available
PHASE II – data generation complete, about 4.6 million
SNPs typed in total.
ENCODE-HAPMAP – A much more detailed variation resource
 48 samples sequenced
 All discovered SNPs (and any others in dbSNP) typed in all
270 HapMap samples
 Current data set – average 1 SNP every 279 bp
HapMap Data Overview
Basic Data: genotypes of the 270 individual samples (frequencies of SNP alleles and
genotypes in each population)
Recent data release (Full Data Set): January 11, 2007, NCBI B35 (includes both Phase
I&II data, genotypes from Illumina 100k and 300k genotyping arrays and the Affymetrix
nsSNPs)
Phase I: 600,000 common SNPs in 270 individuals
Phase II: 4-5 million SNPs in the same individuals
Available for bulk download:
 All genotype data, haplotype phasing data (from PHASE)
 Pedigree trio files
 Raw LD data (D’, R2), recombination rates and hotspots
 Allele and genotype frequencies
 SNP assays and protocols
 Allocated SNPs (dbSNP reference clusters chosen for genotyping)
Adapted from Alanna Morrison, Human Genetics Center, Feb. 2007 lecture
Major Findings of the HapMap Project
 Extensive Redundancy of SNP: over 90% of all SNPs on the
map have highly statistically significant correlation to one or
more neighbors.
 Confirmed the generality of recombination hotspots and long
segments of strong LD (Haplotype blocks), with the average
length ranging from 7.3 (YRI) to 16.3 kb (CEU), and between
65-85% of human genome presented in such blocks.
 Revealed limited haplotype diversity: while each haplotype
block contains 30-70 SNPs, on average only 4-5.6 common
haplotype blocks exist, which can be further identified by a
smaller number of SNPs (tag SNPs).
 The density of common SNPs can be reduced by 75–90% with
essentially no loss of information. That is, the genotyping
burden can be reduced from one common SNP every 500 bp to
one SNP every 2 kb (YRI) to 5 kb (CEU and CHB/JPT).
What can you do from the HapMap Web Site?
 Search for SNPs in a gene or any region of
interest (ROI).
View patterns of LD in the ROI.
Select tagSNPs in the ROI.
 Download information on the SNPs in ROI
for genotype/haplotype data analysis and
visualization in Haploview or other software.
 Generate and retrieve customized subset data.
 Download the entire data set in bulk.
Search HapMap: Example 1
SNPs in human BRCA1 gene have been
reported to be involved in the early onset
of breast cancer.
Find all available genotype and LD data
for SNPs documented for BRCA1 in
HapMap database.
http://www.hapmap.org/
HapMap Search Example 1
Step 1: Open the Genome Browser with the Latest Full Data Set
Click “HapMap Genome
Browser (B35 full data set)”
HapMap Search Example 1
Step 2: Specify the landmark/region of interests
Enter gene name “brca1” to specify
the region of your interest
When there are multiple transcripts,
click one of your choice
HapMap Search Example 1
Step 3: Examine and determine the desired region for display
The mRNA
Examine the region for display
using different scales
Genotype
frequency
Genotyped SNPs in the region, pie
chart shows allelic frequencies (ref
vs other)
HapMap Search Example 1
Step 4: display genotype data for each refSNP
HapMap Search Example 1
Step 5: Select the desired tracks for display
Select the desired analysis results
for display
Click “Update Image” once
the configuration is done
HapMap Search Example 1
Step 6: Configure the tag SNP Picker
Select the desired population
Select the desired tagging methods
Select r2 value to set desired stringency
Set MAF for the lowest threshold of alleles to
be captured by the tagged SNPs
Specify SNPs to be included/excluded as
tagged SNPs
HapMap Search Example 1
Step 7: Configure the LD Plot
Configure LD plot display
Select LD measurement and range
Select desired populations
Customize the color display for LD value
HapMap Search Example 1
Step 8: Tag SNPS and LD Plot
Genotyped SNPs in the region
LD plot shows LD between
different pairs of SNPs
Tagged SNPs based on your
criteria
HapMap Search Example 1
Step 9: Download various data and files
Click “Go”
The genotype data can be used for in depth LD and
Haplotype analysis with the free Haploview program.
Select desired data or file
for download
Haploview-http://www.broad.mit.edu/mpg/haploview/
Haploview
Screenshots
HapMap Data Extraction using HapMart
Select desired population
www.hapmap.org
HapMap Data Extraction using HapMart:
Data filter and export
Perlegen Sciences
 Found in 2000 with the mission of identifying clinically
relevant patterns of genetic variation.
 Over 1.6 millions common SNPs genotyped from 71
individuals from 3 American populations of European,
African and Asian ancestry (about 1 SNP/1871 bp)
 GWA studies on over 100,000 different human
individual.
 Re-sequenced the nuclear DNA genomes of 15 inbred
laboratory mouse strains and generated genotype data.
 Specialized Mouse Genome Brower allows users
visualize the SNPs and LR-PCR primer pairs and
access the SNP genotypes for the 15 strains
http://mouse.perlegen.com/mouse/browser.html
Perlegen Human Genotype Brower
http://genome.perlegen.com/cgi-bin/gbrowse/
Perlegen Human Genotype Brower
 Hosting raw genotyping data for 4.5 million human
SNPs from HapMap, Perlegen, and other projects.
 Generated SNPs data on candidate genes involved in
cardiovascular diseases and inflammatory process.
 Tools for searching, visualization and analysis of
genotype data for association studies.
 Merging SNP data sets from different populations.
Using Genome Variation Server
http://gvs.gs.washington.edu/GVS/index.jsp
Select the search type to
start the search
upload your genotype
data for analysis
Detailed online tutorial
GVS Search Example: rs9939609 (FTO gene)
 Step 1: select query type
1
2
GVS Search Example: rs9939609 (FTO gene)
 Step 2: Select population(s)
GVS Search Example: rs9939609 (FTO gene)
 Step 3: Configure parameters
GVS Search Example: rs9939609 (FTO gene)
 Step 4: Display Results—Genotype data
GVS Search Example: rs9939609 (FTO gene)
 Step 4: Display Results—Genotype data
rs9939609
SNP ID
Sample
GVS Search Example: rs9939609 (FTO gene)
 Step 5: Display results—TagSNPs
TagSNPs Table Display
GVS Search Example: rs9939609 (FTO gene)
 Step 5: Display results—TagSNPs
Bin
TagSNPs Graphic Display
GVS Search Example: rs9939609 (FTO gene)
 Step 6: Display results—LD
GVS Search Example: rs9939609 (FTO gene)
 Step 7: Display results—Summary
SNPs in Ensembl
http://www.ensembl.org/index.html
• Most SNPs imported from dbSNP (rs……):
• Imported data: alleles, flanking sequences, frequencies, ….
• Calculated data: position, synonymous status, peptide shift,
….
• For human also:
•
•
•
•
HGVbase
TSC
Affy GeneChip 100K and 500K Mapping Array
Ensembl-called SNPs (from Celera reads)
• For mouse and rat also:
• Sanger- and Ensembl-called SNPs
SNPs in Ensembl
MapView: SNP density on chromosome
SNPs in Ensembl
ContigView: SNPs in genomic context
SNPs in Ensembl
GeneSeqView: SNPs in genomic sequence
SNPs in Ensembl
TransView & ProtView: SNPs in transcript/ protein
SNPs in Ensembl
What SNPs does my gene contain? > GeneSNPView
SNPs in Ensembl
Info about one specific
SNP?
> SNPView:
• SNP Report
• Genotype and allele
frequencies per population
• Located in transcripts
• SNP Context
• Individual genotypes
https://www.pharmgkb.org/index.jsp
User Question
A recent report (Frayling et al. Science 2007) found a
common variant (rs9939609, A>T) in the FTO
gene (fat mass and obesity associated) is associated
with body mass index and predisposes to obesity
and diabetes.
The adults (16%) carrying homozygous risk allele
A weighed 3 kg more and had 1.67 fold increased
odds of obesity compared to those without the risk
allele.
Use the HapMap and dbSNP to find the genotype
data of this SNP in different populations.
Answer 1: Searching HapMap
Use the refSNP# (must starts with rs)
as the landmark for the search
Click on the pie chart for detailed
population genotype data
Answer 1: Searching HapMap
Population genotype data of the
homozygous risk allele A
Retrieve detailed genotyping data
Answer 2: Searching NCBI’s dbSNP
http://www.ncbi.nlm.nih.gov/sites/entrez?db=Snp
Click on the rs record for detailed
SNP data report
Answer 2: Searching NCBI’s dbSNP
Genotype data from Perlegen’s project
with different population samples
Acknowledgement
In addition to those already stated, some slides of this
workshop were adapted from the sources below:
1. Chattopadhyay A. and M.R. Tennant. “Genetic
Variation Resources”. Lecture slides for 2007 NCBI
Advanced Workshop for Bioinformatics Information
Specialists.
2. Stein L. “Using HapMap.org: A tutorial”.
Presentation slides as part of the Official HapMap
Tutorial.
3. Overduin B. “Sequence Variation in Ensembl”.
Lecture slides for “Ensembl Courses and Workshops”
Recommend Topics for the Second Part of
“Online Resources for Genetic Variation Study”







Functional analysis of SNPs
Tools for SNP discovery and genotyping
Tools for TagSNPs selection
Tools for genome wide association study
Genetic association databases
Others??
Please evaluate this workshop to help me improving
future presentations:
http://www.zoomerang.com/survey.zgi?p=WEB226GJV4RJWR
Have questions or comments about this workshop?
Please contact:
Yi-Bu Chen, Ph.D.
Bioinformatics Specialist
Norris Medical Library
University of Southern California
323-442-3309
[email protected]