Ancient Human
Genome Archive

The Ancient Human Genome Archive (AHGA) is a comprehensive repository and dedicated web-based server for next generation sequence data from publicly available ancient human genomes. AHGA has two components. The first is a server of BAM read alignment files for viewing through the Integrative Genomics Viewer (IGV), a high performance visualization tool for the interactive exploration of genomic sequence data. IGV is freely available from the Broad Institute. Directions for downloading and configuring IGV for use with AHGA can be found here .

The second component is the web application below, which allows for the fast extraction of all read base call and quality score information at a set of genomic positions (given by coordinates, genes, or SNP IDs) for any subset of genomes in the archive. Note: This application does not report called genotypes for sites, but rather outputs the raw bases of all reads covering the position.

Directions
Search the AHGA using a RefSNP accession ID (rs number), an HGNC approved gene symbol or Entrez ID (e.g., SLC24A5 or 283652), or range of physical positions.

Examples:
Single SNP: rs11868112
All sites within 10 kb of SNP: rs11868112+1000
All sites within gene: SLC24A5 or 283652
All sites within 50 kb of gene: SLC24A5+5000 or 283652+5000
All sites within range: Chr9:660,000..661,000

Note: The program assumes either human reference genome build B37/hg19 or B36/hg18, depending on the alignment of the sample genome(s) selected. When selecting more than one genome, do not select genomes aligned to different builds.

Search
Landmark or Region:



Or upload a plain text file containing a list of SNP IDs:


Output Format
Only output read bases as a character string.
Output read bases and base quality scores as character strings.
Output counts for bases A, G, C, and T.

To reduce the size of the output, it is recommended to use the following "Known SNPs Only" filter, which only outputs sites found in dbSNP.

Known SNPs Only (recommended).

Select Genomes
Genomes are grouped by publication. Click on one or more genomes of interest. Multiple genomes can be selected or deselected by holding down the CTRL key. Use the above "Reset" button to deselect all selected genomes. Only genomes mapped to the same build can be selected together.

Di Rienzo  (16)
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Olalde 2014  (2)
Keller 2012  (3)
Raghavan 2014  (1)
Lazaridis 2014  (9)
Fu 2014  (1)
Gamba 2014  (26)
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Rasmussen 2014 (B37)  (1)
Raghavan 2015  (23)
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Fu 2015  (2)
Llorente 2015  (1)
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