Gábor Marth

This paper introduces SimPheny, a framework that uses patient-to-patient phenotype matching to prioritize genes for rare disease diagnosis, outperforming existing methods in cases with limited phenotype associations.

The paper benchmarks somatic variant and indel detection at low allele fractions using short- and long-read data, finding sensitivity and precision around 80% at 300x coverage.

This study uses scRNA-seq and WGS to analyze HSCR patient tissues, identifying impaired neuronal differentiation in aganglionic colon segments.

This study uses long-read scRNA-seq to analyze cancer subclone-specific mutations and transcriptomic differences in CLL patients with BTKC481S mutations.

This paper introduces ScreenDL, a deep learning model that predicts effective cancer therapies using tumor omic and drug screening data, outperforming existing methods in preclinical trials.

The paper reanalyzes RNA-seq data to show pre-mRNA levels vary across cell types, affecting gene length bias and normalization methods, and highlights the impact of bioinformatic processing over assay choice.

This study shows SCLC cells exist in a continuum of plastic states rather than discrete subtypes, with gene expression patterns linked to cancer hallmarks and potential therapeutic targets.

gene.iobio is a web tool that enables clinicians and researchers to interactively analyze and prioritize genomic variants for clinical diagnosis and patient care.

quickBAM accelerates BAM file access by utilizing parallel storage hardware, significantly reducing analysis time for genomic data processing.

The paper analyzes mobile element insertions and structural variants in longitudinal breast cancer samples to assess their timing and impact on tumor progression.

The paper uses deep whole genome sequencing to analyze genetic variants in CDH patients and their families, revealing heterogeneous and multifactorial genetic etiology.

Somalier estimates sample relatedness and detects swaps in cancer and germline studies using efficient genome sketches without requiring germline variant calls.

genepanel.iobio generates disease- and phenotype-associated gene lists by integrating multiple gene:disease resources, improving diagnostic variant prioritization in undiagnosed cases.

This study identifies a large number of structural variants in human genomes using multiple sequencing technologies and presents them as a gold standard for future studies.

This study examines the role of noncoding variation in autism spectrum disorder using whole genome sequencing of 2,076 genomes, finding no significant association after correction for multiple testing.

GIGGLE is a search engine that identifies significant shared genomic loci between query features and large genomic datasets, improving data integration and hypothesis generation.