Lynne V. Abruzzo

The paper shows that pooled correlations in transcriptomic data often reverse sign when analyzed within specific contexts, highlighting the need for context-aware reporting of correlations.

The paper develops a method called Newmanization to reduce tissue signals in transcriptomic data and applies it to digestive tract cancer samples, showing improved clustering and separation compared to mutation data.

WayFindR converts pathway data into graph structures to analyze feedback loops, revealing their underrepresentation in curated databases.

This study characterizes myeloid sarcoma through multi-omic profiling, identifies RAS pathway activation as a hallmark, and shows RAS inhibition reduces tumor burden in mouse models.

plasma is a supervised multiomics method that integrates features into biologically relevant components to predict patient outcomes, outperforming unsupervised and single-omics models.

The paper applies topological data analysis to clinical data from CLL patients to identify complex structures like loops and voids, revealing prognostically important factors.

RCytoGPS converts JSON karyotype data into R objects for analysis and visualization, streamlining computational cytogenetic pathology.

CytoGPS converts ISCN karyotype data into a machine-readable format and binary LGF model for downstream computational analysis.

Polychrome creates and evaluates color palettes with at least 24 distinguishable colors for categorical data visualization, addressing limitations in existing R packages.