3Cnet: pathogenicity prediction of human variants using multitask learning with evolutionary constraints
Motivation Improvements in next-generation sequencing have enabled genome-based
diagnosis for patients with genetic diseases. However, accurate interpretation of human …
diagnosis for patients with genetic diseases. However, accurate interpretation of human …
Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning
Quantifying the pathogenicity of protein variants in human disease-related genes would
have a profound impact on clinical decisions, yet the overwhelming majority (over 98%) of …
have a profound impact on clinical decisions, yet the overwhelming majority (over 98%) of …
DeepPVP: phenotype-based prioritization of causative variants using deep learning
I Boudellioua, M Kulmanov, PN Schofield… - BMC …, 2019 - Springer
Background Prioritization of variants in personal genomic data is a major challenge.
Recently, computational methods that rely on comparing phenotype similarity have shown to …
Recently, computational methods that rely on comparing phenotype similarity have shown to …
VPOT: a customizable variant prioritization ordering tool for annotated variants
Next-generation sequencing (NGS) technologies generate thousands to millions of genetic
variants per sample. Identification of potential disease-causal variants is labor intensive as it …
variants per sample. Identification of potential disease-causal variants is labor intensive as it …
MAGPIE: accurate pathogenic prediction for multiple variant types using machine learning approach
Identifying pathogenic variants from the vast majority of nucleotide variation remains a
challenge. We present a method named Multimodal Annotation Generated Pathogenic …
challenge. We present a method named Multimodal Annotation Generated Pathogenic …
Varipred: Enhancing pathogenicity prediction of missense variants using protein language models
Computational approaches for predicting the pathogenicity of genetic variants have
advanced in recent years. These methods enable researchers to determine the possible …
advanced in recent years. These methods enable researchers to determine the possible …
ClinPred: prediction tool to identify disease-relevant nonsynonymous single-nucleotide variants
Advances in high-throughput DNA sequencing have revolutionized the discovery of variants
in the human genome; however, interpreting the phenotypic effects of those variants is still a …
in the human genome; however, interpreting the phenotypic effects of those variants is still a …
An expanded phenotype centric benchmark of variant prioritisation tools
D Anderson, T Lassmann - Human Mutation, 2022 - Wiley Online Library
Identifying the causal variant for diagnosis of genetic diseases is challenging when using
next‐generation sequencing approaches and variant prioritization tools can assist in this …
next‐generation sequencing approaches and variant prioritization tools can assist in this …
Genetic variant pathogenicity prediction trained using disease-specific clinical sequencing data sets
Recent advances in DNA sequencing have expanded our understanding of the molecular
basis of genetic disorders and increased the utilization of clinical genomic tests. Given the …
basis of genetic disorders and increased the utilization of clinical genomic tests. Given the …
Assessing performance of pathogenicity predictors using clinically relevant variant datasets
AC Gunning, V Fryer, J Fasham, AH Crosby… - Journal of medical …, 2021 - jmg.bmj.com
Background Pathogenicity predictors are integral to genomic variant interpretation but,
despite their widespread usage, an independent validation of performance using a clinically …
despite their widespread usage, an independent validation of performance using a clinically …