Antonio Rausell

Identification and Functional Characterization of Regulatory Variants in DPP9 Associated with COVID-19 Severity

The paper identifies and functionally characterizes regulatory variants in DPP9 associated with severe COVID-19 by analyzing genetic risk factors and their impact on gene expression and immune cell function.

COBT: A gene-based rare variant burden test for case-only study designs using aggregated genotypes from public reference cohorts.

COBT is a gene-based rare variant burden test for case-only studies that outperforms existing methods and identifies novel candidate variants in rare diseases.

PAGAN predicts digenic interactions by generalizing single-gene representations in biological networks

PAGAN predicts digenic interactions by learning network representations of gene pairs from single-gene data in biological networks.

Federated Learning for the pathogenicity annotation of genetic variants in multi-site clinical settings

This study evaluates federated learning for variant pathogenicity annotation in multi-site clinical settings, showing comparable or better performance than centralized models.

NCBoost v2: a classifier for non-coding variants in Mendelian diseases

NCBoost v2 improves pathogenicity scoring for non-coding variants in Mendelian diseases using updated conservation features and splice-altering scores, outperforming existing methods.

The Immune Factors Driving DNA Methylation Variation in Human Blood

This study identifies factors influencing DNA methylation variation in human blood, showing that cytomegalovirus infection and aging drive methylation changes, with cellular composition and DNA sequence as key predictors.

CNVscore calculates pathogenicity scores for copy number variants together with uncertainty estimates accounting for learning biases in reference Mendelian disorder datasets.

CNVscore calculates pathogenicity scores for copy number variants with uncertainty estimates, improving the assessment of CNV pathogenicity in rare disease cohorts.

Integrative genetic and immune cell analysis of plasma proteins in healthy donors identifies novel associations involving primary immune deficiency genes

The paper identifies novel genetic and non-genetic factors associated with plasma protein levels in healthy donors, highlighting their impact on immune response variability.

CNVxplorer: a web tool to assist clinical interpretation of CNVs in rare disease patients

CNVxplorer is a web tool that improves CNV interpretation in rare disease patients by integrating clinical, genomic, and epigenomic features to enhance diagnostic accuracy.

Cell-ID: gene signature extraction and cell identity recognition at individual cell level

Cell-ID extracts per-cell gene signatures from single-cell sequencing data to enable unbiased cell identity recognition across diverse contexts.

Common homozygosity for predicted loss-of-function variants reveals both redundant and advantageous effects of dispensable human genes

The paper identifies 166 dispensable human genes with common loss-of-function variants that show relaxed selective constraints and some evidence of positive selection.

Scoring of pathogenic non-coding variants in Mendelian diseases through supervised learning on ancient, recent and ongoing purifying selection signals in human

The paper develops a supervised learning method to score pathogenic non-coding variants in Mendelian diseases using purifying selection signals, achieving improved predictive performance over existing methods.

Heterozygous gene truncation delineates the human haploinsufficient genome

The paper estimates that 10.8% of human genes are haploinsufficient based on truncating variants in 11,546 individuals.

Sincell: Bioconductor package for the statistical assessment of cell-state hierarchies from single-cell RNA-seq data

Sincell provides a statistical framework for assessing cell-state hierarchies in single-cell RNA-seq data, offering tools to identify stable hierarchies while accounting for noise.

Analysis of stop-gain and frameshift variants in human innate immunity genes

The paper develops a Bayesian classification scheme to rank the pathogenicity of stop-gain and frameshift variants in innate immunity genes using sequence-based features and validates it against known disease variants.