PDIVAS: Pathogenicity predictor for deep-intronic variants causing aberrant splicing
Background Deep-intronic variants that alter RNA splicing were ineffectively evaluated in the
search for the cause of genetic diseases. Determination of such pathogenic variants from a …
search for the cause of genetic diseases. Determination of such pathogenic variants from a …
Large‐scale comparative evaluation of user‐friendly tools for predicting variant‐induced alterations of splicing regulatory elements
H Tubeuf, C Charbonnier, O Soukarieh… - Human …, 2020 - Wiley Online Library
Discriminating which nucleotide variants cause disease or contribute to phenotypic traits
remains a major challenge in human genetics. In theory, any intragenic variant can …
remains a major challenge in human genetics. In theory, any intragenic variant can …
S-CAP extends clinical-grade pathogenicity prediction to genetic variants that affect RNA splicing
KA Jagadeesh, JM Paggi, JS Ye, PD Stenson… - BioRxiv, 2018 - biorxiv.org
There are over 15,000 known variants that cause human inherited disease by disrupting
RNA splicing. While several in silico methods such as CADD, EIGEN and LINSIGHT are …
RNA splicing. While several in silico methods such as CADD, EIGEN and LINSIGHT are …
Introme accurately predicts the impact of coding and noncoding variants on gene splicing, with clinical applications
Predicting the impact of coding and noncoding variants on splicing is challenging,
particularly in non-canonical splice sites, leading to missed diagnoses in patients. Existing …
particularly in non-canonical splice sites, leading to missed diagnoses in patients. Existing …
RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants
Single nucleotide variants (SNVs) in intronic regions have yet to be systematically
investigated for their disease-causing potential. Using known pathogenic and neutral …
investigated for their disease-causing potential. Using known pathogenic and neutral …
CI-SpliceAI—improving machine learning predictions of disease causing splicing variants using curated alternative splice sites
Background It is estimated that up to 50% of all disease causing variants disrupt splicing.
Due to its complexity, our ability to predict which variants disrupt splicing is limited, meaning …
Due to its complexity, our ability to predict which variants disrupt splicing is limited, meaning …
CADD-Splice—improving genome-wide variant effect prediction using deep learning-derived splice scores
Background Splicing of genomic exons into mRNAs is a critical prerequisite for the accurate
synthesis of human proteins. Genetic variants impacting splicing underlie a substantial …
synthesis of human proteins. Genetic variants impacting splicing underlie a substantial …
Aberrant splicing prediction across human tissues
Aberrant splicing is a major cause of genetic disorders but its direct detection in
transcriptomes is limited to clinically accessible tissues such as skin or body fluids. While …
transcriptomes is limited to clinically accessible tissues such as skin or body fluids. While …
Computational prediction of human deep intronic variation
P Barbosa, R Savisaar, M Carmo-Fonseca… - …, 2023 - academic.oup.com
Background The adoption of whole-genome sequencing in genetic screens has facilitated
the detection of genetic variation in the intronic regions of genes, far from annotated splice …
the detection of genetic variation in the intronic regions of genes, far from annotated splice …
SpliceAPP: an interactive web server to predict splicing errors arising from human mutations
AC Huang, JY Su, YJ Hung, HL Chiang, YT Chen… - BMC genomics, 2024 - Springer
Background Splicing variants are a major class of pathogenic mutations, with their severity
equivalent to nonsense mutations. However, redundant and degenerate splicing signals …
equivalent to nonsense mutations. However, redundant and degenerate splicing signals …