Jake Reed

Differential correlation across subpopulations of single cells in subtypes of acute myeloid leukemia

The paper introduces a method to detect differential correlations between protein pairs across subpopulations in AML samples, revealing nonlinear relationships in cytometry data.

Context-dependent correlations mislead transcriptomic network inference in bulk and single-cell data

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.

Clustering Digestive Tract Tumors Using Transcriptomic and Mutation Data

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: Investigating Feedback in Biological Pathways

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

Benchmarking Long-read Sequencing Tools for Chromosome End-specific Telomere Analysis

This study benchmarks two long-read sequencing tools for telomere length analysis, finding Telogator has higher sensitivity while TECAT shows better accuracy and computational efficiency.

Topological Structures in the Space of Treatment-Naive Patients With Chronic Lymphocytic Leukemia

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

Haplotype Diversity and Sequence Heterogeneity of Human Telomeres

This study uses long-read sequencing to analyze human telomere sequences, revealing sequence heterogeneity and non-canonical motifs.