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UMICH Center for Translational Pathology bought Genomatix NextGen Sequencing Analysis Stations
Peter Grant, Chief Executive Officer at Genomatix, USA commented: "Placing our systems in these highly acclaimed labs at the University of Michigan makes us very proud, and confirms that Genomatix' technology is clearly at the leading edge of this important new genomic technology...right in step with the research that is being done here. We have more than a decade of research and development behind many of the tools implemented in this sweeping array of analysis applications, a fact that places us at the very forefront of the NGS data analysis market. We are prepared today for the data avalanche that will inevitably come from the 'next'-next generation of sequencers."
The Genomatix Mining Station (GMS) is based on a proprietary genomic pattern recognition paradigm, or GenomeThesaurus, which allows for input of raw sequence reads plus optional quality files from any deep sequencing hardware. It provides ultra fast mapping of sequences of any length (starting from 8bp) with no practical limits on the number of point mutations and/or insertions and deletions that can be taken into account during the mapping process. Depending on the nature of the experiment, the GMS can provide SNP detection and genotyping, copy number analysis, and small RNA analysis. For ChIPseq data, the GMS delivers clustering and peak finding, and performs automated binding pattern identification. For RNAseq experiments, normalized expression values are calculated at the exon and transcript level. A special GenomeThesaurus is also provided for potential splice junctions, which allows for splice junction analysis and identification of new transcriptional units. For genomic re-sequencing and newly sequenced genomes, a de novo assembly will be provided.
The Genomatix Genome Analyzer (GGA) delivers downstream software tools and databases for the deep biological analysis of data coming from the GMS. It allows for easy integration and visualization in the terabytes of background annotation of the ElDorado genome database. GGA extensively annotates genomic coordinates and surrounding areas derived by the GMS or any other mapping procedure. Clustering and peak finding, analysis for phylogenetic conservation, large scale correlation analysis with annotated genomic elements, meta-analysis of data correlation between different experiments, pathway mining for groups of identified genes, transcription factor binding site (TFBS) analysis ( identification, over-representation, binding partner analysis, framework identification, phylogenetic conservation, regulatory SNP effects) and much more are all processes carried out on the GGA.
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