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Single-cell analysis reveals prognostic fibroblast subpopulations linked to molecular and immunological subtypes of lung cancer

Single-cell analysis reveals prognostic fibroblast subpopulations linked to molecular and immunological subtypes of lung cancer
Single-cell analysis reveals prognostic fibroblast subpopulations linked to molecular and immunological subtypes of lung cancer
R Data files associated with datasets generated in our study "Single-cell analysis reveals prognostic fibroblast subpopulations linked to molecular and immunological subtypes of lung cancer". These include a Seurat object holding integrated scRNA-sequencing data for fibroblasts isolated from multiple human lung cancer datasets (IntegratedFibs_Zenodo.Rdata); a dataframe holding histo-cytometry results from multiplexed immunohistochemistry (mxIHC) analysis performed on whole human lung cancer tissue sections; and additional datafiles required to reproduce the paper's figures. Full details and code demonstrating their use in our analysis are provided on Github (https://github.com/cjh-lab/NCOMMS_NSCLC_scFibs).
Zenodo
Hanley, Christopher Jon
44c46dcb-d239-4d41-9fc5-ca7c2efad6cc
Hanley, Christopher Jon
44c46dcb-d239-4d41-9fc5-ca7c2efad6cc

(2022) Single-cell analysis reveals prognostic fibroblast subpopulations linked to molecular and immunological subtypes of lung cancer. Zenodo doi:10.5281/zenodo.7400873 [Dataset]

Record type: Dataset

Abstract

R Data files associated with datasets generated in our study "Single-cell analysis reveals prognostic fibroblast subpopulations linked to molecular and immunological subtypes of lung cancer". These include a Seurat object holding integrated scRNA-sequencing data for fibroblasts isolated from multiple human lung cancer datasets (IntegratedFibs_Zenodo.Rdata); a dataframe holding histo-cytometry results from multiplexed immunohistochemistry (mxIHC) analysis performed on whole human lung cancer tissue sections; and additional datafiles required to reproduce the paper's figures. Full details and code demonstrating their use in our analysis are provided on Github (https://github.com/cjh-lab/NCOMMS_NSCLC_scFibs).

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More information

Published date: 5 December 2022

Identifiers

Local EPrints ID: 473805
URI: http://eprints.soton.ac.uk/id/eprint/473805
PURE UUID: a3524475-4fa1-44cd-a479-cc14f52419f4

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Date deposited: 01 Feb 2023 17:31
Last modified: 05 May 2023 20:18

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Contributors

Contributor: Christopher Jon Hanley

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