Learn to use HapMap, a database and analysis resource of human variation. The HapMap project identified and cataloged genetic variation in human beings in four populations with African, Asian, and European ancestry. This freely available database and variation browser contains much of the known variation of the Human genome and researchers can use the data to determine variations that affect health, disease, and individual responses to medications and environmental factors. Learn to use the genome browser associated with this project to view HapMap data, retrieve genotypes and find frequencies for genomic regions.

You will learn:

  • to find SNPs of interest with advanced searching
  • how to determine linkage disequilibrium between SNPs
  • how to find candidate tag SNPs to better design genotyping assays
  • where to download and how to use the HaploView software for deeper SNP analysis


This tutorial is a part of the tutorial group Human variations. You might find the other tutorials in the group interesting:

GAD: Genetic Association Database: An archived database associating human genes and polymorphisms with diseases

Madeline 2.0: Human pedigree diagram tools

DrugBank: A chemoinformatics and bioinformatics resource

DGV: Database of Genomic Variants: Database of Genomic Variants, DGV, catalogs and displays structural variation in the human genome

OMIM: Online Mendelian Inheritance in Man (OMIM): A database of human genes, genetic diseases and disorders

CGAP: Characterize the molecular genetic changes that cause a normal cell to become a cancer cell

ENCODE Foundations: ENCyclopedia of DNA Elements

GeneSNPs: An integrated view of gene structure and SNP variations

NIEHS SNPs: National Institute for Environmental Health Sciences Environmental Genome Project (EGP) SNPs

Genetics Home Reference: A collection of data describing the effects of genetic variability on human health and disease

dbGaP: A database of genotypes and phenotypes with extensive variation data and clinical details

SeattleSNPs: Human SNPs in genes

dbSNP: NCBI's SNP database

GeneTests: GeneTests, a current, comprehensive genetic testing resource


Variation & Medical : Resources that include information about sequence variation, phenotypes, or medically-relevant conditions.


Human Genome Project perspectives in 2013: webinar series: In recognition of another decade-based anniversary (and they actually joke in the first session about how it's always possible to find a 10-year something to celebrate on this topic), the NHGRI is host...

Video Tip of the Week: Population Genetics Introduction: We are on the road this week at a workshop in Southern California, so I am going to hand off my tip responsibilities to Lynn Jorde. Another session in the Current Topics in Genome Analysis 2012 course...

Tip of the Week: MutaDATABASE, a centralized and standardized DNA variation database: We all know and love dbSNP, and DGV, and 1000 Genomes, and HapMap, and OMIM, and the couple of other dozen variation databases I can think of off the top of my head. But--even though there's a lot of ...

Tip of the Week: BioGPS for expression data and more: This week's tip introduces BioGPS, or Gene Portal System. We get a lot of questions about two things that BioGPS can help you to tackle: what do I do with a list of genes to find out what they are? An...

Important announcement from HapMap about data archiving: This is from the HapMap team for the human data (not the green HapMap I referenced recently). Older data is going to be removed from the HapMap.org browser and from BioMart. It will still be available...


Recent BioMed Central research articles citing this resource

Karimi Karim et al., Local and global patterns of admixture and population structure in Iranian native cattle Animal population genetics. BMC Genetics (2016) doi:10.1186/s12863-016-0416-z

Chen Xiaomin et al., Association of six CpG-SNPs in the inflammation-related genes with coronary heart disease. Human Genomics (2016) doi:10.1186/s40246-016-0067-1

Lv Xiaozhen et al., The establishment of the objective diagnostic markers and personalized medical intervention in patients with major depressive disorder: rationale and protocol. BMC Psychiatry (2016) doi:10.1186/s12888-016-0953-z

Li Gengxin et al., A new model calling procedure for Illumina BeadArray data Statistical and computational genetics. BMC Genetics (2016) doi:10.1186/s12863-016-0398-x

Polley Shamik et al., Analysis of copy number variation at DMBT1 and age-related macular degeneration Genetic epidemiology and genetic associations. BMC Medical Genetics (2016) doi:10.1186/s12881-016-0311-5