DISCRIMINATOR: Assigning Cohort-Wide Provisional Pathogenicity Classifications to CNVs
Wetzel, A. S.; Major, H.; Parida, M.; Manak, J. R.; Darbro, B. W.
Show abstract
The interpretation of clinical chromosomal microarrays (CMAs) has historically relied on the relevance of identified copy number variants (CNVs) to the clinical phenotype. New interpretation guidelines are focused on standardizing pathogenicity classifications based on genomic location, gene content, and previous publications, rather than the immediate clinical relevance. Here we report on DISCRIMINATOR, which was developed to assign provisional pathogenicity classifications based on genomic location by integrating information on putative benign and pathogenic loci in the human genome. However, its application extends beyond that of a simple classifier. The novel utility of DISCRIMINATOR is its ability to operate on a cohort-level and easily integrate updated definitions of benign and pathogenic regions of the human genome. We used DISCRIMINATOR to assign provisional pathogenicity classifications ( Benign, Secondary, Primary or Non-Coding) to 87,808 CNVs in 3,362 cases ascertained through clinical CMA testing. The majority of identified CNVs were provisionally classified as Benign or Non-Coding and consistent with their prevalence rates, 15q11.2, 16p11.2, and 22q11.2 were the most common Primary CNVs detected. Targeted re-analysis led to the identification of several cases where DISCRIMINATOR identified a Primary CNV within a case that had a non-Abnormal CMA test result, and several cases where only benign and/or non-coding CNVs were identified in reports with a VUS CMA test result. Together these results show the utility of large-scale re-analysis of CMA data and how DISCRIMINATOR addresses this long-standing challenge.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Exome copy number variant detection, analysis and classification in a large cohort of families with undiagnosed rare genetic disease 98%
- The impact of 22q11.2 copy number variants on human traits in the general population 95%
- HiFi long-read genomes for difficult-to-detect clinically relevant variants 94%
Similar papers in this journal
- The Importance of Automation in Genetic Diagnosis: Lessons from Analyzing an Inherited Retinal Degeneration Cohort with the Mendelian Analysis Toolkit (MATK) 95%
- Assessment of the variant prioritisation strategy for genomic newborn screening in the Generation Study 94%
- Reducing Sanger Confirmation Testing through False Positive Prediction Algorithms 94%
Similar papers in this journal
- Exome sequencing as a first-tier test for copy number variant detection : retrospective evaluation and prospective screening in 2418 cases 96%
- Assessing performance of pathogenicity predictors using clinically-relevant variant datasets 93%
- A comparative medical genomics approach may facilitate the interpretation of rare missense variation 92%
Similar papers in this journal
- Third Generation Cytogenetic Analysis (TGCA): diagnostic application of long-read sequencing. 94%
- Concordance of whole-genome long-read sequencing with standard clinical testing for Prader-Willi and Angelman syndromes 93%
- Clinical Validation and Diagnostic Utility of Optical Genome Mapping in Prenatal Diagnostic Testing 93%
Similar papers in this journal
- Evaluating Genome Sequencing Strategies: Trio, Singleton, and Standard Testing in Rare Disease Diagnosis 95%
- Recommendations for clinical interpretation of variants found in non-coding regions of the genome 93%
- Genome-Wide Sequencing as a First-Tier Screening Test for Short Tandem Repeat Expansions 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.