Once sequencing data is available on seqr, Broad CMG analysts will work together with collaborators using the seqr framework to identify strong candidate genes and variants.

Exome and Whole Genome Sequencing Data
Round one of analysis entails identifying candidate variants in known genes associated with the primary disease and phenotype. The majority of filters listed below are relaxed to increase sensitivity to detect potential variants in these known genes.

Subsequent rounds of analysis will attempt to identify rare, likely candidates in genes not previously associated with disease by applying filters to exclude unlikely variants:

Frequency Filters
• Inheritance Patterns
• Functional Annotation
• Genes and Regions
• Quality Filters
• Copy Number Variation

*Copy number variation (CNV) analysis will be conducted on exome sequencing data using GATK gCNV. Genome sequencing data will be processed with GATK-SV to identify a comprehensive set of structural variants.

Please note that we are not funded for targeted functional validation, experimental assays, or clinical follow-up of candidate genes. As such, collaborators will be responsible for detailed clinical and experimental follow-up of candidate variants and genes.

Collaborators will generally be responsible for their own clinical validation of results in an appropriately regulated setting (e.g. a CLIA laboratory) before using them in clinical practice. We request that collaborators update the CMG on the validation status and clinical outcomes of variants.