SurvMarker: an R package for identifying survival-associated molecular features using PCA-based weighted scores
Dona Hasini Gammune, Tongjun Gu · 2026
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Description
Dona Hasini Gammune and Tongjun Gu published this software paper in 2026. It presents SurvMarker, an R package that finds molecular features linked to patient survival in high-dimensional data, where thousands of genes compete and false leads abound.
The method shrinks the data with principal component analysis, tests which components track survival in a Cox model, then scores each gene by its weight across the linked set. An empirical null with false discovery control decides significance, skipping the arbitrary cutoffs older workflows rely on. In tests the package controlled false positives as well as or better than three penalized regression rivals, most of all with few patients and many genes. On a leukemia cohort it beat them all. The authors offer SurvMarker as a clear, reproducible tool for biomarker hunting across omics data types.
Catalog record
| CREATOR | Dona Hasini Gammune, Tongjun Gu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 43 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |