Anélia Horvath

The paper compares transcriptomes of HDACs, TFs, and ion channels in hiPSC-CMs and adult human heart to identify regulatory relationships and cardiotoxicity implications of HDAC inhibitors.

scSNViz provides tools for visualizing and analyzing expressed SNVs in scRNA-seq data, enabling exploration of variant expression patterns and allelic dynamics.

The paper identifies deep skin fibroblasts as a source of pro-inflammatory factors that drive macrophage recruitment and support wound healing in mice.

The paper identifies novel expressed SNVs in tumor and normal scRNA-seq data, revealing a significant number of shared and potentially clinically relevant variants.

SCExecute enables cell barcode-stratified analysis of scRNA-seq data by executing user commands on extracted scBAM files to detect cell-specific variants.

This study shows that analyzing SNVs from individual cell scRNA-seq alignments identifies more SNVs and reveals functional variants compared to pooled analysis.

SCReadCounts estimates cell-level SNVs from scRNA-seq data, enabling mutation analysis and downstream applications in cancer and other studies.

scReQTL correlates SNVs to gene expression in single-cell RNA-seq data by using variant allele fraction instead of population genotypes, enabling analysis of rare variants.

GeTallele estimates and compares variant read probabilities in DNA and RNA sequencing data to assess allele asymmetries and genomic events.

The paper estimates allele-specific expression from 10x Genomics scRNA-seq data and finds that most SNVs are bi-allelic at higher read thresholds, with intronic SNVs showing more monoallelic expression.

RsQTL identifies splicing quantitative trait loci by correlating variant allele fractions with splicing patterns in RNA-seq data from human tissues.

The paper introduces ReQTL, an eQTL analysis method using RNA genetic variation instead of DNA genotypes, showing high performance in identifying molecular associations from RNA-sequencing data.