Gordon K. Smyth

Binning transcript and cell coordinates into spatial vectors lets jazzPanda call smaller, spatially concordant marker sets than Wilcoxon or t-tests on Xenium/CosMx data, while modelling replicates and negative-control background.

This study shows that PU.1 regulates granulocyte maturation by controlling transcriptional programs and 3D chromatin architecture through its binding sites.

The paper identifies SCAF4-CPA and KHDRBS1/SAM68 as key regulators of RNAPII termination under CDK12 inactivation, showing termination dynamics influence elongation rate and response to inhibition.

The paper shows that pre-existing levels of pro-survival proteins and BCL-XL induction determine cell fate after p53 activation, with implications for cancer therapy.

This paper identifies INTS12's role in stabilizing the Integrator-NELF complex to prevent the release of defective RNA Polymerase II complexes, showing its importance in transcription regulation and cellular toxicity.

The paper introduces limma and edgeR pipelines for differential transcript usage analysis that account for read-to-transcript ambiguity, improving power and FDR control in small and large datasets.

This study characterizes MORC2 phosphorylation's role in DNA compaction and chromatin remodelling, showing it regulates ATP hydrolysis and DNA binding.

The paper introduces limpa, a package for quantifying and analyzing MS proteomics data, handling missing values probabilistically to improve differential expression analysis.

edgeR v4 adds a continuous negative binomial for fractional counts, bias-corrected quasi-likelihood for small counts, C-based fitting, and new transcript, exon, methylation and fold-change-threshold analyses.

The paper introduces an improved differential transcript expression analysis pipeline using edgeR v4 and Salmon's Gibbs sampling, showing it is faster and more accurate than previous methods.

This study shows that Suv39h enzymes are essential for organizing euchromatic regions and maintaining gene transcription by tethering H3K9me3 domains to the nuclear lamina.

This paper shows that dividing out quantification uncertainty from transcript counts improves differential expression analysis using edgeR.

The paper demonstrates a workflow for trajectory inference and time course analysis of scRNA-seq data from mouse mammary gland, identifying genes associated with pseudotime.

The paper shows that using T2T-CHM13 instead of GRCh38 improves accuracy in identifying immunoglobulin isotypes from scRNA-seq data by matching the genetic background of the samples.

The paper introduces two methods to handle group heteroscedasticity in pseudo-bulk single-cell RNA-seq data, showing improved error control and power compared to existing methods.

The paper argues that missing values in label-free shotgun proteomics data are informative and proposes a statistical method to estimate the detection probability curve as a function of intensity.

The paper identifies a novel Myc enhancer activated in B cells shortly after activation but finds it is not essential for Myc expression or cell proliferation.

This study develops a synthetic de-methylating module to reactivate stably silenced genes by combining TET1's demethylating activity with transcriptional activators.

The paper benchmarks long-read RNA-sequencing tools using synthetic data to evaluate isoform detection and differential expression analysis performance.

The paper provides R code and processed data objects to reproduce analyses of a scRNA-seq atlas of human breast tissue across normal, preneoplastic, and tumorigenic states.

The paper shows genome reorganization occurs in discrete waves before DNA replication and mitosis, controlling B cell differentiation into plasma cells.

This study examines how T cell activation alters chromatin structure and gene expression, identifying changes in chromatin interactions and domain organization.

The paper introduces qtQDA, a classification method for RNA-seq data that uses quantile transformation and regularized QDA, showing good performance on real datasets.

The paper introduces Rsubread, an R package for RNA-seq alignment and quantification, showing it is faster, cheaper, and more accurate than existing tools.

The paper uses high-resolution genome-wide chromosome conformation capture to analyze transchromosomal interactions in immune cells and finds no evidence of gene regulatory transchromosomal interactions.

limma couples gene-wise linear models with empirical Bayes variance moderation and weights; voom extends it to RNA-seq, and added functions test differential splicing and gene sets.