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An RNA seq-based reference landscape of human normal and neoplastic brain
In order to better understand the relationship between normal and neoplastic brain, we combined five publicly available large-scale datasets, correcting for batch effects and applying Uniform Manifold Approximation and Projection (UMAP) to RNA-seq data. We assembled a reference Brain-UMAP including...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9882693/ https://www.ncbi.nlm.nih.gov/pubmed/36711972 http://dx.doi.org/10.21203/rs.3.rs-2448083/v1 |
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author | Arora, Sonali Szulzewsky, Frank Jensen, Matt Nuechterlein, Nicholas Pattwell, Siobhan S Holland, Eric C. |
author_facet | Arora, Sonali Szulzewsky, Frank Jensen, Matt Nuechterlein, Nicholas Pattwell, Siobhan S Holland, Eric C. |
author_sort | Arora, Sonali |
collection | PubMed |
description | In order to better understand the relationship between normal and neoplastic brain, we combined five publicly available large-scale datasets, correcting for batch effects and applying Uniform Manifold Approximation and Projection (UMAP) to RNA-seq data. We assembled a reference Brain-UMAP including 702 adult gliomas, 802 pediatric tumors and 1409 healthy normal brain samples, which can be utilized to investigate the wealth of information obtained from combining several publicly available datasets to study a single organ site. Normal brain regions and tumor types create distinct clusters and because the landscape is generated by RNA seq, comparative gene expression profiles and gene ontology patterns are readily evident. To our knowledge, this is the first meta-analysis that allows for comparison of gene expression and pathways of interest across adult gliomas, pediatric brain tumors, and normal brain regions. We provide access to this resource via the open source, interactive online tool Oncoscape, where the scientific community can readily visualize clinical metadata, gene expression patterns, gene fusions, mutations, and copy number patterns for individual genes and pathway over this reference landscape. |
format | Online Article Text |
id | pubmed-9882693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
spelling | pubmed-98826932023-01-28 An RNA seq-based reference landscape of human normal and neoplastic brain Arora, Sonali Szulzewsky, Frank Jensen, Matt Nuechterlein, Nicholas Pattwell, Siobhan S Holland, Eric C. Res Sq Article In order to better understand the relationship between normal and neoplastic brain, we combined five publicly available large-scale datasets, correcting for batch effects and applying Uniform Manifold Approximation and Projection (UMAP) to RNA-seq data. We assembled a reference Brain-UMAP including 702 adult gliomas, 802 pediatric tumors and 1409 healthy normal brain samples, which can be utilized to investigate the wealth of information obtained from combining several publicly available datasets to study a single organ site. Normal brain regions and tumor types create distinct clusters and because the landscape is generated by RNA seq, comparative gene expression profiles and gene ontology patterns are readily evident. To our knowledge, this is the first meta-analysis that allows for comparison of gene expression and pathways of interest across adult gliomas, pediatric brain tumors, and normal brain regions. We provide access to this resource via the open source, interactive online tool Oncoscape, where the scientific community can readily visualize clinical metadata, gene expression patterns, gene fusions, mutations, and copy number patterns for individual genes and pathway over this reference landscape. American Journal Experts 2023-01-10 /pmc/articles/PMC9882693/ /pubmed/36711972 http://dx.doi.org/10.21203/rs.3.rs-2448083/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Arora, Sonali Szulzewsky, Frank Jensen, Matt Nuechterlein, Nicholas Pattwell, Siobhan S Holland, Eric C. An RNA seq-based reference landscape of human normal and neoplastic brain |
title | An RNA seq-based reference landscape of human normal and neoplastic brain |
title_full | An RNA seq-based reference landscape of human normal and neoplastic brain |
title_fullStr | An RNA seq-based reference landscape of human normal and neoplastic brain |
title_full_unstemmed | An RNA seq-based reference landscape of human normal and neoplastic brain |
title_short | An RNA seq-based reference landscape of human normal and neoplastic brain |
title_sort | rna seq-based reference landscape of human normal and neoplastic brain |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9882693/ https://www.ncbi.nlm.nih.gov/pubmed/36711972 http://dx.doi.org/10.21203/rs.3.rs-2448083/v1 |
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