Genomics and Rare Diseases

The paper identifies 8 novel SNPs in the CD40LG gene using bioinformatics tools and suggests they may be diagnostic markers for hyper-IgM syndrome.

This study identifies eleven novel pathogenic nsSNPs in the STAT3 gene associated with Job's syndrome using in silico analysis of SNPs from dbSNP/NCBI.

The paper predicts four novel SNPs in the SBDS gene associated with Shwachman-Diamond Syndrome using in silico methods and identifies potential disease-causing variants.

The paper identifies two novel deleterious mutations in the XK gene using in silico analysis, suggesting their potential as diagnostic markers for McLeod syndrome.

This paper compares missense variants in monogenic diseases and cancer, finding similarities and differences in their structural and functional impacts.

The paper evaluates MEFV gene variants using REVEL scores to establish a gene-specific threshold, reducing variants of uncertain significance from 61.6% to 17.6%.

The paper identifies five novel damaging nsSNPs in the IL2RG gene using computational tools and predicts their potential impact on gene function and expression.

VSIM is a web tool for variant interpretation in personal genomes, supporting genetic counseling and premarital screening by simulating children's genomes.

The paper identifies two novel deleterious mutations in the PRSS1 gene using in silico analysis of SNPs.

The paper develops regSNPs-intron, a random forest classifier to prioritize intronic SNVs for disease, validated using ASSET-seq functional assays.

This study evaluates a precision health platform integrating whole genome sequencing and noninvasive clinical assessments in 1190 healthy participants, identifying significant genetic and phenotypic findings linked to disease risk.

EXtrACtor enables efficient querying of ExAC and gnomAD databases for multiple genes or regions, with filtering options and a user-friendly interface.

The paper introduces a Bayesian framework to prioritize risk genes for complex diseases by integrating gene-set information with variant counts, identifying novel epilepsy risk genes and linking them to immune pathways and drug targets.

This study uses whole exome sequencing to diagnose 352 Korean pediatric patients with undiagnosed neurodevelopmental disorders, identifying pathogenic variants in 57.4% of cases.

VCF/Plotein is a web application that enables secure and interactive viewing and filtering of exome sequencing data for researchers and medical professionals.

The paper introduces a probabilistic method based on the birthday model to detect rare disease-related genetic variants in complex disorders, showing its effectiveness in identifying potential causative genes.

The paper identifies deleterious non-synonymous SNPs in the SMPX gene associated with hearing impairment using bioinformatics tools.

The paper describes the establishment of a harmonized clinical sequencing network for the eMERGE III Network, enabling standardized protocols and integration of genomic results into electronic health records.

The paper quantifies shared single nucleotide variants between somatic and germline mutation databases, finds excess sharing, and explains it through mutation rate correlations and contamination.

The paper uses somatic mutation data from cancers to predict genes involved in germline mutations' phenotypic effects, showing their predictive power is independent of germline-based methods.

The paper identifies 41 deleterious SNPs in the IKBKAP gene through in silico analysis, prioritizing them for further genetic studies on Familial dysautonomia.

The paper introduces two variant pathogenicity prediction models, VSRFM and VSRFM-s, which incorporate splicing information and allele frequency to improve prediction accuracy.

The paper demonstrates that software-assisted manual review of NGS data achieves equivalent accuracy to Sanger sequencing in confirming variant calls for hereditary cancer screening.

This study uses whole exome sequencing to identify genetic causes of short stature in 20 patients, finding molecular diagnoses in 45% with discrepancies between clinical and genetic diagnoses.

This study evaluates the use of whole blood transcriptome sequencing for diagnosing rare diseases, finding an 8.5% diagnostic rate across 56 undiagnosed cases.

This paper identifies five deleterious nsSNPs in the human p53 gene using multiple computational tools and validates their potential to contribute to oncogenesis.

mTADA jointly analyzes de novo mutation data from multiple neuropsychiatric disorders to identify shared and specific risk genes.

Divine prioritizes disease-causing genes in whole exome sequencing data by integrating phenotype and biological knowledge, outperforming existing methods in a retrospective study.

The paper develops a method to detect diploid-triploid mixoploidy using whole genome sequencing data and validates it with clinical cytogenetic testing.

The paper investigates the genetic contributions to intellectual disability, finding rare variants are more common in severe cases and common variants contribute to all severity levels.