Benefits for Researchers

GenomeQuest SDM

Next generation sequencing (NGS) is transforming genome-based research. Now, more than ever, researchers need powerful discovery tools and complete management of their sequence data.

GenomeQuest introduces a new category of product – called sequence data management (SDM) – that meets these needs for NGS discovery.

GenomeQuest features for researchers includes:

• A browser-based, data management dashboard

• Sequence assembly and annotation

• Data mining on sequence alignments and text annotations

• Data set joins (mining across multiple experiments)

• Result saves/re-mining (interactive discovery)

• Data/result sharing with colleagues through dashboards

• Data export to other discovery tools, including desktop visualization

• Single-point-of-access to reference databases

• Easy configuration

• Built-in workflows for common discovery challenges

• And all of these features scalable to NGS volumes

Easy to Use Workflows

Interactive Discovery

GenomeQuest workflows package all bioinformatics details -- including the reference data, the queries, the algorithms, the interfacing to third party tools, the compute environment, and the results -- into an easy-to-use upload/compute/analyze loop for the researcher.  Workflows are available for digital gene expression, antibody optimization, variant detection, rapid annotation for metagenomics, BLAST search, and patent search.

Aggregated reference databases include Transcriptomes, Genomes Transcriptomes, Genomes, Reference Genomes, Genbank, and GenomeQuest Pat which span genes, genomes, proteins, drugs, and patents.

Examples of workflow uses cases include:

• Starting with billions of Illumina reads of a single human, a researcher can map them to the reference human genome, mine a set of genes for high-quality novel variations, and visualize a select few to determine whether the variation changes the protein product of the gene.

• From millions of Illumina reads from a drug resistant strain of a bacteria, a researcher can map them to the reference bacterial genome and catalog the differences.

• With 80 million SOLiD reads from an experimental time series fromArabidopsis thaliana, a researcher can view the gene expression profiles over the time series.

Researchers, employing a “top-down” discovery methodology, can use GenomeQuest for global mining to identify local areas of interest, and then export that data to desktop analysis/visualization tools for further investigation.

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