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PreprintCC BYbioRxiv

XpBrew and PanXpresso - automatic RNA-seq processing workflow and comprehensive collection of gene expression data

  • S. Natarajan
  • C. Sterling
  • N. Choudhary
  • N. Khatun
  • M.-S. Brieske
  • H. E. Busch
  • B. Pucker1
  1. 1University of Bonn, Institute for Cellular & Molecular Botany (IZMB)
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Abstract

Rapid developments in sequencing technologies have reduced the costs of transcriptomic experiments and resulted in a plethora of publicly available RNA-seq datasets. This is a valuable resource that can be harnessed to obtain novel biological insights through data upcycling. In this wake, we introduce XpBrew, an end-to-end Python workflow that was applied to generate PanXpresso, a comprehensive collection of gene expression datasets covering the taxonomic breadth of plants, animals, fungi, bacteria and archaea. XpBrew (https://github.com/PuckerLab/XpBrew) and PanXpresso (https://doi.org/10.60507/FK2/OBIGQH) are freely available.

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Cite

BibTeXRIS
BibTeX
@misc{natarajan2026xpbrew,
  title = {{XpBrew and PanXpresso - automatic RNA-seq processing workflow and comprehensive collection of gene expression data}},
  author = {S. Natarajan and C. Sterling and N. Choudhary and N. Khatun and M.-S. Brieske and H. E. Busch and B. Pucker},
  howpublished = {bioRxiv},
  year = {2026},
  month = aug,
  doi = {10.64898/2026.08.27.747620},
  url = {https://www.biorxiv.org/content/10.64898/2026.08.27.747620v1},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - XpBrew and PanXpresso - automatic RNA-seq processing workflow and comprehensive collection of gene expression data
AU  - S. Natarajan
AU  - C. Sterling
AU  - N. Choudhary
AU  - N. Khatun
AU  - M.-S. Brieske
AU  - H. E. Busch
AU  - B. Pucker
PY  - 2026
DA  - 2026/08/27
PB  - bioRxiv
DO  - 10.64898/2026.08.27.747620
UR  - https://www.biorxiv.org/content/10.64898/2026.08.27.747620v1
AB  - Rapid developments in sequencing technologies have reduced the costs of transcriptomic experiments and resulted in a plethora of publicly available RNA-seq datasets. This is a valuable resource that can be harnessed to obtain novel biological insights through data upcycling. In this wake, we introduce XpBrew, an end-to-end Python workflow that was applied to generate PanXpresso, a comprehensive collection of gene expression datasets covering the taxonomic breadth of plants, animals, fungi, bacteria and archaea. XpBrew (https://github.com/PuckerLab/XpBrew) and PanXpresso (https://doi.org/10.60507/FK2/OBIGQH) are freely available.
ER  -