1. ABOUT THE DATASET
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Title:	Dataset for Single-cell nanobiopsy enables multigenerational longitudinal transcriptomics of cancer cells

Creator(s): 
Fabio Marcuccio [1,2], Chalmers C. Chau [2],  Georgette Tanner [2], Marilena Elpidorou [2], Martina A. Finetti [2], Shoaib Ajaib [2], Morag Taylor [2], Carolina Lascelles [2], Ian Carr [2], Iain Macaulay [3], Lucy F. Stead [2], and Paolo Actis [2]

Organisation(s): 1, Imperial College London; 2, University of Leeds; 3, Earlham Institute

Rights-holder(s): Fabio Marcuccio, Chalmers C. Chau, Georgette Tanner,  Marilena Elpidorou, Martina A. Finetti, Shoaib Ajaib, Morag Taylor, Carolina Lascelles, Ian Carr, Iain Macaulay, Lucy F. Stead, and Paolo Actis.


Publication Year: 2024

Description: The repository is divided in 3 main folders:

1) Main: contains the data used to generate the images, graphs and plots of the figures in the main manuscript. This folder contains the raw data. To learn about the methods, please refer to the main manuscript and supporting information file, where methods used for the experiments and data analysis are comprehensively described.

2) SI: contains the data used to generate the images, graphs, and plots of the figures in the Supporting Information file. This folder contains the raw data. To learn about the methods, please refer to the main manuscript and supporting information file, where methods used for the experiments and data analysis are comprehensively described.

3) DATA-Bioinformatics: contains the Sequencing Data, scripts and pipelines used to generate the graphs and plots for the nanobiopsy and the whole-cell datasets. These data are also freely accessible on the GitHub repository at the following link link: https://github.com/GliomaGenomics/GBM_NB


Cite as: 
Fabio Marcuccio, Chalmers C. Chau, Georgette Tanner,  Marilena Elpidorou, Martina A. Finetti, Shoaib Ajaib, Morag Taylor, Carolina Lascelles, Ian Carr, Iain Macaulay, Lucy F. Stead, Paolo Actis (2024): 
Dataset for  Single-cell nanobiopsy enables multigenerational longitudinal transcriptomics of cancer cells. [Dataset]. https://doi.org/10.5518/1464

Related publication:  Single-cell nanobiopsy enables multigenerational longitudinal transcriptomics of cancer cells


Contact: l.f.stead@leeds.ac.uk, p.actis@leeds.ac.uk


2. TERMS OF USE
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You may download to a local hard disk extracts for your personal, non-commercial and for results reproducibility use only. 2024. Fabio Marcuccio, Chalmers C. Chau, Georgette Tanner,  Marilena Elpidorou, Martina A. Finetti, Shoaib Ajaib, Morag Taylor, Carolina Lascelles, Ian Carr, Iain Macaulay, Lucy F. Stead, and Paolo Actis.
This dataset is licensed under cc_by_v4_0.

3. FUNDING INFORMATION
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Funding organisation:
Engineering and Physical Science Research Council (EPSRC) UK,
Biotechnology and Biological Sciences Research Council (BBSRC) UK,
Medical Research Council UK,
University of Leeds

Grant no.:
THe Brain Tumour Charity - GN-000482
European Commission H2020 grant - 812398
UK Research and Innovation - MR/T020504/1


4. CONTENTS
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File listing

All files in this data set are in .abf format, this format can be accessed by pClamp software (any version), originlab software (any version), matlab or python with the pyABF package.

Below for the list of files:
Main.zip
SI.zip
DATA - Bioinformatics.zip

5. METHODS
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For full method, please refer to the associated publication.