Advanced variant exploration
Alamut Genova, the latest evolution of Alamut Visual, is a full genome browser designed to explore and investigate variations of the human genome.
The software gathers in one place a wide set of external data and algorithms of recognized quality to help scientists interpret human variants in the exact genomic context.
Alamut Genova has been developed to ease biologists and physicians’ daily genetic analysis activities. The Alamut database contains more than 28’000 coding genes, non-protein coding genes and pseudogenes. This database (shared with the high throughput annotation engine for NGS data, Alamut Batch) is frequently updated.
Information comes from different public databases such as NCBI, EBI, and UCSC, as well as other sources including gnomAD, ESP, Cosmic or ClinVar.
Other informative data provided by Alamut Genova includes nucleotide conservation through many vertebrate species, as the phastCons and phyloP scores, amino acid conservation data through orthologue alignments and information on protein domains.
Moreover, Alamut Genova integrates several missense variant pathogenicity prediction tools and algorithms such as SIFT, PolyPhen, AlignGVGD or MutationTaster. It also provides a dedicated view for in silico study of variants’ effect on RNA splicing, allowing the assessment of their potential impact on splice junctions and visualization of cryptic or de novo splice sites.
Alamut Genova efficiently visualizes BAM alignments in their genomic context, as well as associated VCF files in order to easily study variants detected by NGS analyses. Several BAM files can be loaded simultaneously for multi-sample studies such as trios analysis.
Alamut Genova is used in cutting-edge university medical centers, hospitals and private genetic analysis laboratories worldwide. It is much appreciated by its users (see Testimonials) since it allows to save a significant amount of time thanks to its user-friendly graphical interface. Consequently, laboratories increase their productivity. It strengthens users’ analyses work quality and efficiency, relying on updated databases, applying HGVS nomenclature, and supporting good practices and recommendations of the genetic community.
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