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Estimating Exome Genotyping Accuracy by Comparing to Data from Large Scale Sequencing Projects

Estimating Exome Genotyping Accuracy by Comparing to Data from Large Scale Sequencing Projects

A new paper was published in Genome Medicine about how genotyping accuracy is estimated by comparing variant data with data from large scale sequencing projects such as the 1000 Genomes Project.

Quality metrics are now availible at GeneTalk for all uploaded VCF files. V.  Heinrich developed a metrics algorithm that compares variant data of the uploaded VCF file against a matching population group from the 1000 Genomes Project data.

The genotyping accuracy is the plotted in two graphics in GeneTalk

Genotyping Accuracy and Non-Metric MDS

The plots display how well a sample matches into a population grpoup of the 1000 Genomes Project data (Non-Metric MDS) and estimates the genotyping accuracy in percent (Genotyping Accuracy).

 

Abstract:

With exome sequencing becoming a tool for mutation detection in routine diagnostics there is increasing need for platform-independent methods of quality control. We present a genotype-weighted metric that allows comparing all the variant calls of an exome to a high-quality reference dataset of an ethnically matched population. The exome-wide genotyping accuracy is estimated from the distance to this reference set, and does not require any further knowledge about data generation or the bioinformatics involved. The distances of our metric are visualized by non-metric multidimensional scaling and serve as a standardizable score for the quality assessment of exome data.

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