William Evan Johnson

This study reanalyzes longitudinal serum proteomics data from tuberculosis patients to assess how nutritional-metabolic recovery during treatment varies by baseline BMI, finding no significant BMI-dependent trajectories but an overall increase in a 36-protein summary axis.

The paper examines transcriptional changes in severe undernutrition during latent TB infection and finds inconsistent associations with TB progression across cohorts.

ComBatFamQC provides an R package for batch-effect diagnosis and harmonization in neuroimaging data, integrating visualization, statistical tests, and harmonization methods.

This paper examines how batch effects impact machine learning classifier performance across multiple studies and compares adjustment methods.

The paper examines the relationship between erythrocyte count and mortality in older adults, finding a critical threshold below which mortality risk sharply increases.

The paper introduces BatchQC, an R package for assessing and correcting batch effects in high-throughput data with reproducible tools and workflows.

This study generates 50 complete Mtb genomes, identifies core and accessory gene clusters, and proposes a new pangenome reference resource to improve TB research.

This study shows that inhibiting CSF1R in male MIA offspring improves sociability and memory, while female offspring show no improvement, highlighting sex-specific therapeutic potential.

MetaScope improves species-level classification of microbial communities using 16S rRNA data, achieving higher accuracy than existing tools like QIIME2 and DADA2.

This paper describes RUPB-61, an orally available PfPKG inhibitor that prevents liver infection by malaria sporozoites and shows activity against drug-resistant isolates.

This study shows that helminth infection leads to prolonged neutrophil proliferation and survival, distinct from responses to bacterial or fungal infections.

The paper introduces InMoose, an open-source Python environment for bulk transcriptomic analysis, offering tools for data simulation, batch correction, and differential analysis.

This study identifies Myc dysregulation in macrophages as a driver of TB susceptibility by linking lipid peroxidation and IFN-I pathway hyperactivity.

The paper curates 49 TB transcriptomic datasets into a resource to assess gene signature replicability and demonstrates improved diagnostic accuracy through ensembling.

This study uses total RNA sequencing to compare gene expression and microbial profiles between oral premalignant lesions, cancer, and healthy tissues, identifying shared molecular and microbial features associated with progression to cancer.

SCTK2.0 provides an integrated toolkit for scRNA-seq analysis with a graphical interface, enabling non-programmers to perform end-to-end workflows and generate reproducible reports.

ICAT improves identification of cell states after perturbations in single-cell RNA sequencing by using self-supervised feature weighting and control-guided clustering.

This study compares gene set scoring methods with original models for TB gene signatures, finding that gene set scoring can achieve equivalent or better performance than original models.

The paper evaluates taxonomic classification accuracy of 16S amplicon sequencing data using different pipelines and reference databases, finding that whole-genome tools outperform 16S-specific ones.

Celda identifies transcriptional modules and cell subpopulations in scRNA-seq data, outperforming existing methods in detecting biological programs and cell types.

The paper introduces a pipeline for generating, visualizing, and reporting quality control metrics for scRNA-seq data, improving standardization across platforms.

The paper evaluates the impact of two-step batch correction on gene expression analysis and proposes strategies to mitigate its effects on statistical inference.

The paper identifies a Gabra2 variant that increases methamphetamine sensitivity using QTL analysis in mice and validates it with CRISPR correction.

This study investigates sex differences in behavioral and brainstem transcriptomic changes in mice exposed to neonatal opioids, finding sex-specific neuroadaptations linked to NOWS-like behaviors.

The paper identifies a dynamic hnRNP H RNA targetome in the striatum that responds to methamphetamine, affecting gene expression and behavior.

This paper develops an ensemble learning approach to improve genomic classifiers by integrating predictions across batches rather than removing batch effects from merged data, showing better performance in independent validation.

ComBat-Seq adjusts RNA-Seq count data for batch effects using negative binomial regression, improving statistical power and false positive control in differential expression analyses.

The paper identifies 5' UTR variants in Hnrnph1 that reduce 5' UTR usage and hnRNP H protein levels, linking these changes to reduced methamphetamine sensitivity.

DecontX is a Bayesian method to remove ambient RNA contamination in scRNA-seq data, improving cell cluster separation and marker gene accuracy.