Sean K. Maden

lute improves cell composition estimation in bulk RNA-seq by accounting for varying cell sizes, using simulated and real datasets to demonstrate its accuracy.

The paper benchmarks cellular deconvolution methods using a multi-assay dataset from human prefrontal cortex, finding Bisque and hspe to be the most accurate.

recountmethylation provides processed blood DNA methylation data and analysis tools, showing genetic ancestry and cell fractions explain most DNAm variation and validating DMPs between sexes.

The paper compares retained intron detection in short and long RNA-seq reads, finding significant disagreement among tools and poor precision/recall.

The paper analyzes 35,360 DNAm array samples from GEO, identifies tissue sources, evaluates quality assessments, and provides a database with annotated data through an R/Bioconductor package.

The paper uses a consensus machine learning approach to identify gene targets associated with pediatric AML risk, finding recurrently selected genes like HOXA9 and MEIS1 across multiple algorithms.