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Avadis NGS March 14, 2012

Feature Highlight

Find Significant SNPs

One of the features in Avadis NGS 1.3 is the ability to identify Significant SNPs easily for a variety of different use cases including normal-tumor comparison, multi-group comparison, low frequency mutations, rare variant analysis and somatic mutations.

'Find Significant SNPs' runs on the multi sample report generated by SNP Detection and identifies significant SNPs using an intuitive filtering frame work. It essentially filters the alleles by the specified confidence and commonality criteria which are defined in terms of total coverage, strand bias and the supporting reads percentage.

SNP Analysis in Avadis NGS is present in two experiment types - DNA Variant Analysis and RNA-Seq Analysis. SNP Detection identifies the SNPs by comparing the reads from the sample genome against the reference genome.

Above: Identify significant SNPs using an intuitive filtering framework.

New Video Tutorials

Support for MiSeq Data in Avadis NGS
Watch this video to learn how the data in a MiSeq generated "run folder" is automatically loaded into the Avadis NGS software during small RNA alignment and DNA variant analysis and how to use the QC steps of Avadis NGS to check if the amplicons have sufficient coverage in all the samples.

Analysis of Ion Torrent Data in Avadis NGS
Watch this video to learn how to align the long, variable-length reads generated by Ion Torrent sequencers and how pre-alignment QC plots can be used to set appropriate alignment parameters for aligning Ion Torrent reads. Users of the Ion AmpliSeq™ Cancer Panel can find out how to easily import the targeted mutation list and verify a genotype call at the mutation sites.

If you are interested in either trying Avadis NGS with your own data or scheduling a demo presentation for your organization, send us an email that describes your experiments and desired research endpoints.

If you are interested in buying Avadis NGS for your lab, please contact sales for plans and pricing.

- The Avadis NGS Team

© 2012 Strand Scientific Intelligence, Inc.

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