602 citations · 605 across the 10 of their papers we have counts for
10 papers
Mitigating Batch Effects in Histopathology via Language-Mediated Robust Embedding Generation
Yishu Zhang, Shushan Wu, Zhenzhong Zhang +8
Pathology foundation models (PFMs) have demonstrated strong potential across clinical and scientific applications, yet their performance is often hindered by batch effects, which a…
Towards interpretable prediction of recurrence risk in breast cancer using pathology foundation models
Jakub R. Kaczmarzyk, Sarah C. Van Alsten, Alyssa J. Cozzo +5
Transcriptomic assays such as the PAM50-based ROR-P score guide recurrence risk stratification in non-metastatic, ER-positive, HER2-negative breast cancer but are not universally a…
Pairwise Nonlinear Dependence Analysis of Genomic Data
Siqi Xiang, Wan Zhang, Siyao Liu +4
In The Cancer Genome Atlas (TCGA) data set, there are many interesting nonlinear dependencies between pairs of genes that reveal important relationships and subtypes of cancer. Suc…
Jackstraw Inference for AJIVE Data Integration
Xi Yang, Katherine A. Hoadley, Jan Hannig +1
In the age of big data, data integration is a critical step especially in the understanding of how diverse data types work together and work separately. Among data integration meth…
A Hierarchical Spike-and-Slab Model for Pan-Cancer Survival Using Pan-Omic Data
Sarah Samorodnitsky, Katherine A. Hoadley, Eric F. Lock
Pan-omics, pan-cancer analysis has advanced our understanding of the molecular heterogeneity of cancer, expanding what was known from single-cancer or single-omics studies. However…
Measure of Strength of Evidence for Visually Observed Differences between Subpopulations
Xi Yang, Jan Hannig, Katherine A. Hoadley +2
For measuring the strength of visually-observed subpopulation differences, the Population Difference Criterion is proposed to assess the statistical significance of visually observ…
Bidimensional linked matrix factorization for pan-omics pan-cancer analysis
Eric F. Lock, Jun Young Park, Katherine A. Hoadley
Several modern applications require the integration of multiple large data matrices that have shared rows and/or columns. For example, cancer studies that integrate multiple omics…
Joint and individual analysis of breast cancer histologic images and genomic covariates
Iain Carmichael, Benjamin C. Calhoun, Katherine A. Hoadley +8
A key challenge in modern data analysis is understanding connections between complex and differing modalities of data. For example, two of the main approaches to the study of breas…
A Pan-Cancer and Polygenic Bayesian Hierarchical Model for the Effect of Somatic Mutations on Survival
Sarah Samorodnitsky, Katherine A. Hoadley, Eric F. Lock
We built a novel Bayesian hierarchical survival model based on the somatic mutation profile of patients across 50 genes and 27 cancer types. The pan-cancer quality allows for the m…
Joint and individual variation explained (JIVE) for integrated analysis of multiple data types
Eric F. Lock, Katherine A. Hoadley, J. S. Marron +1
Research in several fields now requires the analysis of data sets in which multiple high-dimensional types of data are available for a common set of objects. In particular, The Can…