Ingileif B. Hallgrímsdóttir

This study compares 10X Genomics and Parse Biosciences scRNA-seq technologies, finding platform-specific biases in gene counts and composition, with Parse showing GC-content bias and potential nuclear RNA enrichment.

The paper introduces a framework to determine cis or trans regulation contributions to gene expression differences between strains or species and applies it to yeast, human-chimpanzee hybrid, and mouse data.

The paper uses hybrid crosses to analyze regulatory variation in mouse tissues, finding cell-type-specific trans-acting effects and highlighting the limitations of bulk tissue analysis.

CellSweep removes technical contamination from single-cell genomics data, improving accuracy in downstream analysis.

The paper characterizes transcriptomes across 8 tissues in 8 mouse strains to identify expression variation linked to genetic differences and phenotypic traits.

The paper identifies androgen receptor-mediated regulation of sexually dimorphic gene expression in the mouse kidney and finds limited conservation in human kidney.

The paper introduces a normalization method for single-cell RNA-seq data that meets three criteria and outperforms existing methods on benchmarks.

This paper introduces an alignment-free method for genome-wide association studies using k-mer counts, demonstrating its ability to detect associations with structural variations and sequences absent from reference genomes.