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Our department is looking for a software solution to support analysis and reporting of somatic cancer variants (currently panels, but eventually exomes). It looks like most of the currently available reporting software (Cartagenia, Next Code) is designed to support germline analysis (rare disease analysis). We would be interested in any software packages that are available to specifically support somatic cancer variant analysis. Know of any?
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Gerald -- I work at GenomOncology. We offer a Clinical Workbench, installed within your firewall, where the input is the BAM/VCF and QC files to enable professional interpretation (in a high-assurance fully traceable and audit-able manner) and generate a clinically actionable report in less than 20 minutes from start to finish. The report is template driven and 100% customizable to your labs needs.
Vanderbilt’s MyCancerGenome, plus FDA, NCCN and ACSO guidelines, drive the clinical interpretation and also allows the lab to add relevant Clinical Trials and content. We have an exclusive license for MyCancerGenome and a solid relationship with the Vanderbilt team. If your institution has its own rules, those can easily be added too.
Feel free to message me -- I'm happy to talk further. -
WuXi NextCODE support somatic cancer
Hi Gerald, I am with WuXi NextCODE. We do support somatic cancer. If you want a demo, please let me know. I am happy to walk you through it.Comment
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Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
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Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.07-01-2026, 11:43 AM
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