Dataset
Dataset for “Single-molecule quantification of RNA modifications using a probabilistic framework”
- Documentation:
- This dataset supports the study “Path Signatures Enable Model‑Free Mapping of RNA Modifications” (arXiv:2511.08855v1), authored by Maud Lemercier, Paola Arrubarrena, Salvatore Di Giorgio, Julia Brettschneider, Thomas Cass, Isabel S. Naarmann‑de Vries, Anastasia Papavasiliou, Alessia Ruggieri, Irem Tellioglu, Chia Ching Wu, F. Nina Papavasiliou, and Terry Lyons. The dataset contains raw and processed single‑molecule measurements used to develop and validate a model‑free, signature‑based approach for detecting RNA modifications. It is provided as a compressed archive () together with a checksum file (). The archive includes molecule‑level data from mouse, dengue virus, and E. coli, as well as IVT controls and native RNA measurements. The file hierarchy is as follows: BM_mouse-chr10_mettl3koP2E224hLPS-g_M-sup-I-m6A-I-m6A.sorted_chr10.bam.txt BM_mouse-chr10_ctr2-24hLPS-g_M-sup-I-m6A.sorted_chr10.bam.txt Bm_mouse-chr10-IVT_ctr1-24hLPS-g_IVT-sup-I-m6A.sorted_chr10.bam.txt Dengue_Data/ 20241002_DENV_IVT_gRNA.txt.gz 20241029_DENV_gRNA-pA_oligo.txt.gz IVT.txt.gz Native_sfRNA.txt.gz Ecoli_Data/ Native_rRNa_1623.txt.gz IVT_rRNa_1623.txt.gz
Actions
Authors/Creators
Contributors
+ Lemercier, M
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Mathematical Institute
- Role:
- Contributor
+ Arrubarrena, P
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Mathematical Institute
- Role:
- Contributor
+ Di Giorgio, S
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Mathematical Institute
- Role:
- Contributor
+ Brettschneider, J
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Mathematical Institute
- Role:
- Contributor
+ Cass, T
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Mathematical Institute
- Role:
- Contributor
+ Engineering and Physical Sciences Research Council
More from this funder
- Funder identifier:
- https://ror.org/0439y7842
- Grant:
- EP/S026347/1
- Publisher:
- University of Oxford
- Publication date:
- 2026
- Digital size:
- 400Gb
- Digital storage location:
- Stored within ORA DeepData service, please contact the ORA team to discuss access
- DOI:
- Language:
-
English
- Keywords:
- Pubs id:
-
2377648
- Local pid:
-
pubs:2377648
- Deposit date:
-
2026-02-18
- ARK identifier:
Terms of use
- Copyright holder:
- Lemercier et al
- Copyright date:
- 2026
- Notes:
- Acknowledgements to the various colleagues and funding agencies providing the resources allowing this data to be created can be found in the accompanying paper.
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