Pablo Mínguez

This study uses genomic data from 11,084 patients to build a variant database and identify disease-associated signals, leading to molecular diagnoses in 32 unsolved rare disease cases.

AFQuery computes capture-aware allele frequencies for clinical genomics cohorts, reducing errors and bias in variant classification.

The paper predicts gene-rare disease associations using a network-based algorithm to improve variant prioritization and guide functional validation.

This study identifies novel genetic risk loci for COVID-19 hospitalization in admixed American populations through a large GWAS.

The paper develops GLOWgenes, a disease-aware network-based algorithm to prioritize new candidate genes for rare genetic diseases by evaluating heterogeneous molecular networks.

This study replicates previous findings on the association between androgen receptor polyQ alleles and COVID-19 severity in men, finding no significant association.

The paper builds a cohort-specific allelic frequency database to prioritize variants and genes in non-solved inherited retinal dystrophies, identifying 8 potential causative variants and 18 genes for further study.

VIsoQLR is a tool for identifying, quantifying, and fine-tuning mRNA isoforms using long-read sequencing data in low-throughput splicing assays.

The paper maps the impact of PTM site deletion on genetic diseases by analyzing PTM-variant concurrences and disease associations.