Charlotte Soneson

The paper introduces SACCELERATOR, a framework for spatially aware clustering that improves benchmarking by incorporating expert feedback and consensus analysis across diverse datasets.

The paper identifies MEP-1 as a novel substrate of DPF-3, showing cleavage after threonine and demonstrating its impact on reproductive fitness.

This study uses an organoid model to show luminal epithelial cells drive endometrial regeneration through WNT7A and cell-cell communication during the menstrual cycle.

This study shows that rbm8a deficiency in zebrafish causes hematopoietic defects by impairing non-canonical Wnt/PCP signaling, leading to reduced thrombocytes and LPM anomalies.

The paper systematically mutagenizes human bZIP domains and uses deep mutational scanning to quantify interactions, revealing complex genetic architecture and enabling synthetic bZIP design.

The paper creates a comprehensive atlas of transcription factor interactions in S. pombe using experimental methods and introduces a web tool for exploring the data.

The paper identifies virus-induced ubiquitination in monocytes, showing it regulates protein localization and inhibits antiviral responses.

The paper introduces tidyomics, an ecosystem bridging Bioconductor and tidy R to streamline omic analysis using data from the Human Cell Atlas.

DifferentialRegulation identifies differentially regulated genes by analyzing unspliced mRNA abundance across experimental conditions using a Bayesian hierarchical model.

The paper develops qPISA to quantify protease substrate turnover, revealing subsite cooperativity in DPP4 and distinguishing it from DPF-3.

einprot provides an R package for reproducible analysis of quantitative proteomics data, generating reports with interactive visualizations and customizable workflows.

The paper identifies TRIM71's mechanism of mRNA silencing through recruitment of TNRC6/GW182 and shows competition among silencing pathways.

The paper evaluates a new method for classifying splicing status in single-cell and single-nucleus RNA-seq data, finds it conservative but ambiguous, and introduces new tools to improve classification.

This paper benchmarks differential gene expression analysis methods for inter-species RNA-Seq data using a phylogenetic simulation framework to evaluate their performance across species.

mutscan provides an R package for end-to-end analysis of MAVE data, supporting statistical modeling and visualization of variant effects.

This paper meta-analyzes single-cell method benchmarks to identify challenges in extensibility, interoperability, and reproducibility.

This study identifies Hand2 as a key regulator of mesothelium progenitors in zebrafish and shows its reactivation in mesothelioma, linking developmental processes to disease.

Alevin-fry provides a fast, memory-efficient, and accurate method for quantifying single-cell and single-nucleus RNA-seq data, including RNA velocity inputs.

monaLisa identifies transcription factors from experimental data by integrating with Bioconductor packages for motif analysis.

This paper evaluates synthetic scRNA-seq data generators, finding they often introduce artificial effects and fail to accurately mimic real data for method comparisons.

treeclimbR identifies optimal hierarchical resolutions for detecting entities associated with phenotypes in multi-resolution data.

CellMixS quantifies and visualizes batch effects in scRNA-seq data by developing a cell-specific mixing score and comparing metrics for their performance.

The paper confirms that considering unexpected fragment origins improves transcript quantification accuracy in RNA-seq simulations and shows that Srivastava et al.'s methodology enhances this accuracy.

This study compares RNA velocity results across different quantification tools for droplet scRNA-seq data, showing significant differences in abundance estimates and their impact on velocity analysis.

This paper develops a simulation platform and analysis tools for multi-condition differential state analysis in scRNA-seq data, comparing cell-level mixed models and pseudobulk approaches.

The paper evaluates how alignment and mapping methods affect transcript quantification accuracy and introduces a new method called selective alignment.

Tximeta automatically identifies reference transcriptomes and gathers metadata for RNA-seq analysis using checksums, improving reproducibility and reducing errors.

This paper provides an overview of single-cell RNA sequencing analysis using Bioconductor, highlighting its tools and methods for handling high-dimensional data.

This study evaluates Nanopore native RNA sequencing on complex transcriptomes, finding it has potential but faces challenges in full-length transcript capture and origin inference.

diffcyt identifies differential cell populations in high-dimensional cytometry data using high-resolution clustering and empirical Bayes tests.