The performance of deleteriousness prediction scores for rare non-protein-changing single nucleotide variants in human genes

In recent years, whole genome sequencing has increasingly been used as a replacement of whole exome sequencing for identifying causal variants of human diseases. In response to this trend, several ‘genome-level’ deleteriousness prediction scores have been proposed to implement the scores designed specifically for missense or splicing variants. The aim of this study was to investigate the prediction accuracy of those genome-level scores for rare non-protein-changing single nucleotide variants (npcSNVs) in and near human genes. We compared 15 genome-level deleteriousness prediction scores and eight conservation scores using receiver operating characteristic (ROC) and area under curve (AUC). We found that fathmm-MKL coding score1 was the best score for npcSNVs (AUC=0.875), outperforming other genome-level deleteriousness prediction scores and conservation scores.

As the cost of whole genome and exome sequencing has reduced considerably, clinical use of sequencing data is becoming more popular. Even though more candidate SNVs were identified and...

from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/2jzrrAh
via IFTTT