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A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification
The increased application of high-throughput approaches in translational research has expanded the number of publicly available data repositories. Gathering additional valuable information contained in the datasets represents a crucial opportunity in the biomedical field. To facilitate and stimulate...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5820610/ https://www.ncbi.nlm.nih.gov/pubmed/29527288 http://dx.doi.org/10.12688/f1000research.10960.2 |
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author | Roelands, Jessica Decock, Julie Boughorbel, Sabri Rinchai, Darawan Maccalli, Cristina Ceccarelli, Michele Black, Michael Print, Cris Chou, Jeff Presnell, Scott Quinn, Charlie Jithesh, Puthen Syed, Najeeb Al Bader, Salha B.J. Bedri, Shahinaz Wang, Ena Marincola, Francesco M. Chaussabel, Damien Kuppen, Peter Miller, Lance D. Bedognetti, Davide Hendrickx, Wouter |
author_facet | Roelands, Jessica Decock, Julie Boughorbel, Sabri Rinchai, Darawan Maccalli, Cristina Ceccarelli, Michele Black, Michael Print, Cris Chou, Jeff Presnell, Scott Quinn, Charlie Jithesh, Puthen Syed, Najeeb Al Bader, Salha B.J. Bedri, Shahinaz Wang, Ena Marincola, Francesco M. Chaussabel, Damien Kuppen, Peter Miller, Lance D. Bedognetti, Davide Hendrickx, Wouter |
author_sort | Roelands, Jessica |
collection | PubMed |
description | The increased application of high-throughput approaches in translational research has expanded the number of publicly available data repositories. Gathering additional valuable information contained in the datasets represents a crucial opportunity in the biomedical field. To facilitate and stimulate utilization of these datasets, we have recently developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB). In this note, we describe a curated compendium of 13 public datasets on human breast cancer, representing a total of 2142 transcriptome profiles. We classified the samples according to different immune based classification systems and integrated this information into the datasets. Annotated and harmonized datasets were uploaded to GXB. Study samples were categorized in different groups based on their immunologic tumor response profiles, intrinsic molecular subtypes and multiple clinical parameters. Ranked gene lists were generated based on relevant group comparisons. In this data note, we demonstrate the utility of GXB to evaluate the expression of a gene of interest, find differential gene expression between groups and investigate potential associations between variables with a specific focus on immunologic classification in breast cancer. This interactive resource is publicly available online at: http://breastcancer.gxbsidra.org/dm3/geneBrowser/list. |
format | Online Article Text |
id | pubmed-5820610 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-58206102018-03-08 A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification Roelands, Jessica Decock, Julie Boughorbel, Sabri Rinchai, Darawan Maccalli, Cristina Ceccarelli, Michele Black, Michael Print, Cris Chou, Jeff Presnell, Scott Quinn, Charlie Jithesh, Puthen Syed, Najeeb Al Bader, Salha B.J. Bedri, Shahinaz Wang, Ena Marincola, Francesco M. Chaussabel, Damien Kuppen, Peter Miller, Lance D. Bedognetti, Davide Hendrickx, Wouter F1000Res Data Note The increased application of high-throughput approaches in translational research has expanded the number of publicly available data repositories. Gathering additional valuable information contained in the datasets represents a crucial opportunity in the biomedical field. To facilitate and stimulate utilization of these datasets, we have recently developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB). In this note, we describe a curated compendium of 13 public datasets on human breast cancer, representing a total of 2142 transcriptome profiles. We classified the samples according to different immune based classification systems and integrated this information into the datasets. Annotated and harmonized datasets were uploaded to GXB. Study samples were categorized in different groups based on their immunologic tumor response profiles, intrinsic molecular subtypes and multiple clinical parameters. Ranked gene lists were generated based on relevant group comparisons. In this data note, we demonstrate the utility of GXB to evaluate the expression of a gene of interest, find differential gene expression between groups and investigate potential associations between variables with a specific focus on immunologic classification in breast cancer. This interactive resource is publicly available online at: http://breastcancer.gxbsidra.org/dm3/geneBrowser/list. F1000 Research Limited 2018-02-09 /pmc/articles/PMC5820610/ /pubmed/29527288 http://dx.doi.org/10.12688/f1000research.10960.2 Text en Copyright: © 2018 Roelands J et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Data Note Roelands, Jessica Decock, Julie Boughorbel, Sabri Rinchai, Darawan Maccalli, Cristina Ceccarelli, Michele Black, Michael Print, Cris Chou, Jeff Presnell, Scott Quinn, Charlie Jithesh, Puthen Syed, Najeeb Al Bader, Salha B.J. Bedri, Shahinaz Wang, Ena Marincola, Francesco M. Chaussabel, Damien Kuppen, Peter Miller, Lance D. Bedognetti, Davide Hendrickx, Wouter A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification |
title | A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification |
title_full | A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification |
title_fullStr | A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification |
title_full_unstemmed | A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification |
title_short | A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification |
title_sort | collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification |
topic | Data Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5820610/ https://www.ncbi.nlm.nih.gov/pubmed/29527288 http://dx.doi.org/10.12688/f1000research.10960.2 |
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