Wondering how to get more out of your data?What more you can do with sequencing data after evaluating sequence variants?
Whether you can eliminate arrays and solely use NGS?
We have come a long way in a short amount of time with NGS (next-generation sequencing) technologies. Next-generation sequencing platforms for whole-exome sequencing (WES), whole-genome sequencing (WGS) and targeted NGS panels each have their benefits and drawbacks and one may be better suited for a particular application than another. Costs are coming down and ease of use is improving making NGS even more popular. Often evaluation of sequence variation from NGS is complemented by interrogation of structural variation (e.g. copy number) using microarrays.
Microarrays, including SNP arrays that can also detect copy neutral LOH, have been the platform of choice for detection of copy number variation and CNVs play an important role in tumor progression. But if you have samples that have undergone sequencing to detect pathogenic sequence variations, wouldn’t it be great to squeeze more out of this data and get copy number from it? Can you get quality copy number results from your sequencing data? With improved software and new algorithms, this is becoming a reality!
BioDiscovery’s algorithm, BAM (Pooled Reference) in Nexus Copy Number, takes on the challenge! This read-depth based method uses a pooled reference thereby eliminating the need for matched tumor normal samples and it also generates BAF (B-Allele Frequencies) allowing for improved calling as well as identification of allelic events. Want to see how this new algorithm stacks up to other methods for CNV detection? Read this white paper that compares CNV detection in TCGA colon adenocarcinoma (COAD) samples between
- WES data processed with the BAM (Pooled Reference) algorithm
- WES data processed with the BAM ngCGH (matched) algorithm
- Affymetrix SNP 6.0 arrays