Sara Ballouz

The paper examines sex differences in the immune system at the single-cell level, identifying sex-biased genes and eQTLs linked to autoimmune diseases.

The paper shows transcriptomic individuality in genetically identical armadillo quadruplets is driven by monocyte lineage expansion and stable gene expression differences.

This study uses single-cell RNA sequencing to analyze immune aging in 982 donors, revealing sex-specific changes in immune cell composition and function during aging.

Longitudinal gene expression in identical armadillo quadruplets reveals a major role for developmental stochasticity.

This study evaluates the impact of using a Pan-human consensus genome on RNA-seq alignment accuracy, finding significant improvements in mapping error reduction and splice junction quantification.

The paper uses X-chromosome inactivation ratios across tissues to infer developmental timing and cell numbers during human lineage commitment.

CoCoCoNet identifies conserved gene modules and compares co-expression networks across 14 species, demonstrating conservation in nucleolus genes and translating autism mechanisms to model organisms.

The paper discusses the limitations of the current human reference genome and suggests a consensus reference may offer advantages for variant calling.

The paper assesses the replicability of disease expression signals across pedigrees and identifies genes missed by systems methods.

This study evaluates STAR aligner performance across alignment parameters and biological tasks, finding technical metrics uninformative and performance mostly robust except in challenging genomic regions.

The paper introduces MetaNeighbor, a framework to assess cell type replicability across scRNA-seq datasets and identifies replicable neuronal subtypes with robust marker genes.

The paper examines functional convergence in autism spectrum disorder across different study designs and finds a correlation between gene involvement in autism and functional convergence strength.

This paper evaluates the robustness of gene set analysis results and introduces a method to identify non-specific and non-robust findings, while providing software for bias correction.

EGAD provides fast functional analysis of gene networks by predicting novel gene group members and assessing network performance using guilt-by-association methods.

The paper introduces AuPairWise, a method to estimate RNA-seq replicability using co-expression patterns, showing that 5% expression perturbation is detectable with AUROC~0.73.