LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Haplostrips: revealing population structure through haplotype visualization

Photo by mbaumi from unsplash

Summary Population genetic analyses often identify polymorphic variants in regions of the genome that indicate the effect of non-neutral evolutionary processes. However, in order to obtain deeper insights into the… Click to show full abstract

Summary Population genetic analyses often identify polymorphic variants in regions of the genome that indicate the effect of non-neutral evolutionary processes. However, in order to obtain deeper insights into the evolutionary processes at play, we often resort to summary statistics, sacrificing the information encoded in the complexity of the original data. Here, we present haplostrips, a tool to visualize polymorphisms of a given region of the genome in the form of independently clustered and sorted haplotypes. Haplostrips is a command-line tool written in Python and R, that uses variant call format files as input and generates a heatmap view. Haplostrips is available at: https://bitbucket.org/dmarnetto/haplostrips. It can be applied in several fields and in all living systems for which a phased haplotype is available to visualize complex effects of, among others: introgression, domestication, selection, demographic events. Haplostrips can reveal hidden patterns of genetic variation without losing the basic information encoded in variant sequences.

Keywords: structure haplotype; revealing population; population structure; haplostrips revealing; haplotype visualization; population

Journal Title: Methods in Ecology and Evolution
Year Published: 2017

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.