Golden Helix Genome Browser Download
Sixta Strissel
GenomeBrowse runs as a native desktop application on your computer. No longer do you have to sacrifice speed and interface quality to obtain a consistent cross-platform experience. It was developed with performance in mind to deliver a faster and more fluid browsing experience than any other genome browser available. GenomeBrowse is also integrated into the powerful Golden Helix VarSeq variant annotation and interpretation platform. If you love the visualization experience of GenomeBrowse, check out VarSeq for filtering, annotating, and analyzing your data before utilizing the same visualization interface.
In terms of people adding their own genomes, it really is top top priority! But what we are doing now is curating and shipping genomes on request with a turn around of less than a week if you email genome...@goldenhelix.com. Our current customers of SVS can curate their own genomes, but we want to improve the experience for folks doing it from GenomeBrowse. The decision was to ship and let people with many common species have the tool to start using (which we might agree is a large portion of users) or wait till we have this feature in there.
Showstopper: not being able to import my own genome and annotation. In my project, are working with sea lice, which have no public genome yet, and hence are not in the list. Otherwise I might have recommended GenomeBrowse, as one of many alternatives in a list of "free" tools, as it is now, it is unfortunately no alternative to IGV at all. So here come my 2ct for making a successful genome browser:
I have used the GH browser successfully on a number of BAM files. Now I have a genome in CRAM format and I can't seem to do anything with it. GH apparently won't load it. I can not understand the unix tools that may be available for converning files. Is there any simple way around this problem? Is there any way to make GH recognize and load a CRAM file? Maybe I don't have the most recent version?
To the right of the eyeball in Genome Browse is the zoom scroll bar. You can also zoom by using the magnifying glass to the right above the zoom scroll bar then highlighting a section on which you want to zoom in on. To select and move left to right instead of zooming when you click and drag within genome browse, switch to the pointer icon next to the magnifying glass. To the left of the pointer is a link out to an external genome browser or genomic region sites from NCBI, UCSC, and Ensembl. The search bar to the left of this can be used to jump to any desired chromosomal location as mentioned above. The back and forward arrows are used to go back and forth between the previous views that a user had been looking at in Genome Browse. To the left of those arrows is the Settings icon shaped like a gear. The default settings of Genome Browse can be adjusted here.
Golden Helix and Expression Analysis have created an end-to-end analysis solution for RNA-Seq data. This sophisticated yet user-friendly offering addresses the obstacles of next-gen sequencing analytics by providing a collection of tightly coupled cloud-based and desktop analysis tools that are scalable, affordable, and comprehensive. Primary and secondary analyses are delivered through the cloud, where data is stored and managed with an easy-to-use interface. When users are ready to "make sense" of this data (tertiary analysis), Golden Helix provides differential expression workflows optimized for RNA-Seq data in its SNP & Variation Suite. The third component of the solution is a powerful, multi-sample genome browser optimized for streaming data directly from the cloud.
In this webcast, Greta Linse Peterson will present updated workflows in SNP & Variation Suite 8 (SVS) and GenomeBrowse for agricultural genetic research. SVS includes a robust suite of analytical tools and a revolutionary genome browser in one program to support a wide-variety of species including plant, animal, and parasites. New tools make it easy to adjust for inbreeding and incomplete pedigrees, making it even easier than before to identify variants related to pest and disease resistance, increased feed efficiency, milk production, and more.
GWAS was accomplished with the single-locus mixed linear model procedure implemented in Golden Helix SVS v8.1.1 software (Golden Helix, Inc, Bozeman, MT, USA, www.goldenhelix.com). Specifically, the efficient mixed model association (EMMA) approach66 was used to directly estimate the variance components σ2g and σ2e, reducing the problem to a maximization search in just one direction. To correct for population structure in the absence of pedigree data, a kinship matrix was computed once using all markers. The kinship matrix was then used to solve the EMMA equation for every marker. The EMMA procedure and equations have been described in details in SNP & Variation Suite Manual Release 8.4.3 (Golden Helix, Inc.) and in Kang et al.66 and summarized below:
Both the additive and dominant models were used in GWAS. Under the additive model, testing is designed specifically to reveal associations which depend additively based on the allele classification. When alleles are classified according to frequencies, the associations will depend additively on the minor allele, where having two minor alleles (DD) rather than having no minor alleles (dd) is twice as likely to affect the outcome in a certain direction as is having just one minor allele (Dd) rather than no minor alleles (dd) (SVS Manual release 8.4.3, www.goldenhelix.com). Under the dominant model, allele classification according to frequency specifically tests the association of having at least one minor allele D (either Dd or DD) versus not having it at all (dd) (SVS Manual release 8.4.3). Both models were used in GWAS in this study to enable the capture of most existing associations. The Benjamini-Hochberg (BH) false discovery rate (FDR) correction was applied to raw p-values and genome wide significance was declared at P-Value BH FDR
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