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PreprintCC BY-NC-NDbioRxiv

KSTAR v1.2: A faster and more and accessible KSTAR for kinase activity inference

  1. 1University of Virginia

Abstract

Motivation: KSTAR is an algorithm with high flexibility for inferring kinase activity from any phosphoproteomic pipeline. However, in its first instantiation (v0.1) it requires Python programming and lots of memory and computational resources. Hence, we wished to improve speed and accessibility for broader uptake by researchers. Results: Here, we provide an updated algorithm that improves speed and memory, without affecting accuracy, along with some new features for increased usability and insight. KSTAR v1.2 has also been integrated into Galaxy for programming-free activity analysis and ProteomeScout for dataset preparation and interactive plotting. Availability and implementation: KSTAR is available at https://github.com/NaegleLab/KSTAR or on Galaxy on https://usegalaxy.org/. KSTAR Network resource assets are managed on Figshare at: https://doi.org/10.6084/m9.figshare.14944305.

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BibTeX
@misc{crowl2026kstar,
  title = {{KSTAR v1.2: A faster and more and accessible KSTAR for kinase activity inference}},
  author = {S. Crowl and J.-L. Custer and G. Salazar Lopez and C. Lei-Dadey and A. A. Shimpi and K. M. Naegle},
  howpublished = {bioRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.14.751568},
  url = {https://www.biorxiv.org/content/10.64898/2026.09.14.751568v1},
  note = {CC BY-NC-ND},
}
RIS
TY  - UNPB
TI  - KSTAR v1.2: A faster and more and accessible KSTAR for kinase activity inference
AU  - S. Crowl
AU  - J.-L. Custer
AU  - G. Salazar Lopez
AU  - C. Lei-Dadey
AU  - A. A. Shimpi
AU  - K. M. Naegle
PY  - 2026
DA  - 2026/09/14
PB  - bioRxiv
DO  - 10.64898/2026.09.14.751568
UR  - https://www.biorxiv.org/content/10.64898/2026.09.14.751568v1
AB  - Motivation: KSTAR is an algorithm with high flexibility for inferring kinase activity from any phosphoproteomic pipeline. However, in its first instantiation (v0.1) it requires Python programming and lots of memory and computational resources. Hence, we wished to improve speed and accessibility for broader uptake by researchers. Results: Here, we provide an updated algorithm that improves speed and memory, without affecting accuracy, along with some new features for increased usability and insight. KSTAR v1.2 has also been integrated into Galaxy for programming-free activity analysis and ProteomeScout for dataset preparation and interactive plotting. Availability and implementation: KSTAR is available at https://github.com/NaegleLab/KSTAR or on Galaxy on https://usegalaxy.org/. KSTAR Network resource assets are managed on Figshare at: https://doi.org/10.6084/m9.figshare.14944305.
ER  -