Wednesday, 19 September 2012

GenomeBrowse TM by Golden Helix;Broad's IGV's competitor?

http://www.goldenhelix.com/GenomeBrowse/index.html

Golden Helix has released a genome browser that gives you a visual representation of variants on a genome whilst pulling variant data from various sources "from the cloud" Not sure if it means Golden Helix is hosting the dbs or it's just pulling from the respective db sites. 

should be interesting to see how this matches up with IGV


Features

VCF File Format Support

  • Lightning fast, direct VCF visualization as a sample-based variant plot.
  • Automatically sort and index files for quick access.

Tabular View of Any Data Source

  • Step through a list of putative causal variants or highly differentiated genes.
  • Get an infinitely scroll-able tabular view of any data source with details on each feature.
  • Use tables to zoom GenomeBrowse and focus on a feature.

Build Custom Annotation Tracks

  • Convert any text file, whether a BED file or a tabular dump of UCSC, into your own annotation track.
  • Curate reference sequences and genomes of new species.

Access Your Large Cloud-Based Sequencing Data

  • Illumina BaseSpace account integration coming soon to view your alignments and variant calls directly streamed from the cloud.

GenomeBrowse was launched on September 12th via a live webcast.

View the webcast launch »


In a one-hour webcast launch on September 12th, Gabe Rudy, Vice President of Product Development, will showcase GenomeBrowse including showing you how to:

  • View cloud-based public and private NGS samples with the context of public annotations like the 1000 Genomes variant list, NHLBI Exome Sequencing Project, and OMIM catalog.

  • Validate putative causal variants by investigating the read-based evidence from BAM files. Mismatch emphasis, read depth, and quality scores gives you confidence in your variants and lets you throw out false-positives.

  • Analyze a trio to browse variant inheritance between parents and child. Follow up on putative recessive, de Novo, or compound heterozygous variants to ensure their quality.

  • Investigate differentially expressed genes and splicing structure through the coverage profiles and pile-ups of RNA-seq data.

  • Navigate and fluidly browse from the single base to whole genome view without losing the context of what your data is telling you and without the disorienting jitters of other browsers.

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