Data

Quick URL: All the datasets are available at http://hsb.upf.edu/hsb_data/

Dataset: Detection of Positive Selection Events in the 1000 Genomes Data

Our data is available as a local instance of the UCSC Genome Browser. So go to the Browser, find your region and activate the tracks you want to visualize. Or simply use the entry mask. The raw data is now downloadable from this webserver.

Each statistic result can be shown as a raw score or its genome-wide “rank score”. See this article for a more detailled description. The “rank scores” often are convenient for visualization, as they display statistics under positive selection as positive values (peaks). The raw scores are useful to visualize balancing selection (e.g. in the HLA region using Tajima´s D and segregating sites). Scaling of result tracks is done using the option “configure” below the browser window.

Click on the figure below to access it:http://pgb.ibe.upf.edu/cgi-bin/hgTracks?hgHubConnect.destUrl=..%2Fcgi-bin%2FhgTracks&clade=mammal&org=Human&db=hg19&position=chr15%3A48316779-48530978&hgt.suggest=DAB1&hgt.suggestTrack=knownGene&Submit=submit&hgsid=2630&hgt.newJQuery=1&knownGene=pack&knownGene=pack

Our tracks are organized in 4 sections:
– Selection Statistics based on Allele Frequency Spectrum
– Selection Statistics based on Linkage Disequilibrium Structure
– Selection Statistics based on Population Differentiation
– Descriptive Statistics

The raw data is also accessible through the “Tables” function of the browser, or from this server. Alternatively, from the table function it can be sent to Galaxy  (Goecks et al., 2010) for convenient downstream processing.

Dataset: Human Genome Variation and the Concept of Genotype Networks

We also provide data from the paper ‘Human Genome Variation and the Concept of Genotype Networks’ published by our group. See this post for more details, or click on this linkto to access the data.

Dataset: a Machine Learning Framework to Detect and Classify Hard Selective Sweeps in Human Populations

We applied a machine learning framework to combine the results of all the tests for positive selection provided here. This data will become available soon. For more information, see this page.