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­A curated transcriptomic dataset collection relevant to embryonic development associated with in vitro fertilization in healthy individuals and patients with polycystic ovary syndrome

The collection of large-scale datasets available in public repositories is rapidly growing and providing opportunities to identify and fill gaps in different fields of biomedical research. However, users of these datasets should be able to selectively browse datasets related to their field of intere...

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Detalles Bibliográficos
Autores principales: Mackeh, Rafah, Boughorbel, Sabri, Chaussabel, Damien, Kino, Tomoshige
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5365227/
https://www.ncbi.nlm.nih.gov/pubmed/28413616
http://dx.doi.org/10.12688/f1000research.10877.1
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author Mackeh, Rafah
Boughorbel, Sabri
Chaussabel, Damien
Kino, Tomoshige
author_facet Mackeh, Rafah
Boughorbel, Sabri
Chaussabel, Damien
Kino, Tomoshige
author_sort Mackeh, Rafah
collection PubMed
description The collection of large-scale datasets available in public repositories is rapidly growing and providing opportunities to identify and fill gaps in different fields of biomedical research. However, users of these datasets should be able to selectively browse datasets related to their field of interest. Here we made available a collection of transcriptome datasets related to human follicular cells from normal individuals or patients with polycystic ovary syndrome, in the process of their development, during in vitro fertilization. After RNA-seq dataset exclusion and careful selection based on study description and sample information, 12 datasets, encompassing a total of 85 unique transcriptome profiles, were identified in NCBI Gene Expression Omnibus and uploaded to the Gene Expression Browser (GXB), a web application specifically designed for interactive query and visualization of integrated large-scale data. Once annotated in GXB, multiple sample grouping has been made in order to create rank lists to allow easy data interpretation and comparison. The GXB tool also allows the users to browse a single gene across multiple projects to evaluate its expression profiles in multiple biological systems/conditions in a web-based customized graphical views. The curated dataset is accessible at the following link: http://ivf.gxbsidra.org/dm3/landing.gsp.
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spelling pubmed-53652272017-04-14 ­A curated transcriptomic dataset collection relevant to embryonic development associated with in vitro fertilization in healthy individuals and patients with polycystic ovary syndrome Mackeh, Rafah Boughorbel, Sabri Chaussabel, Damien Kino, Tomoshige F1000Res Data Note The collection of large-scale datasets available in public repositories is rapidly growing and providing opportunities to identify and fill gaps in different fields of biomedical research. However, users of these datasets should be able to selectively browse datasets related to their field of interest. Here we made available a collection of transcriptome datasets related to human follicular cells from normal individuals or patients with polycystic ovary syndrome, in the process of their development, during in vitro fertilization. After RNA-seq dataset exclusion and careful selection based on study description and sample information, 12 datasets, encompassing a total of 85 unique transcriptome profiles, were identified in NCBI Gene Expression Omnibus and uploaded to the Gene Expression Browser (GXB), a web application specifically designed for interactive query and visualization of integrated large-scale data. Once annotated in GXB, multiple sample grouping has been made in order to create rank lists to allow easy data interpretation and comparison. The GXB tool also allows the users to browse a single gene across multiple projects to evaluate its expression profiles in multiple biological systems/conditions in a web-based customized graphical views. The curated dataset is accessible at the following link: http://ivf.gxbsidra.org/dm3/landing.gsp. F1000Research 2017-02-23 /pmc/articles/PMC5365227/ /pubmed/28413616 http://dx.doi.org/10.12688/f1000research.10877.1 Text en Copyright: © 2017 Mackeh R 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
Mackeh, Rafah
Boughorbel, Sabri
Chaussabel, Damien
Kino, Tomoshige
­A curated transcriptomic dataset collection relevant to embryonic development associated with in vitro fertilization in healthy individuals and patients with polycystic ovary syndrome
title ­A curated transcriptomic dataset collection relevant to embryonic development associated with in vitro fertilization in healthy individuals and patients with polycystic ovary syndrome
title_full ­A curated transcriptomic dataset collection relevant to embryonic development associated with in vitro fertilization in healthy individuals and patients with polycystic ovary syndrome
title_fullStr ­A curated transcriptomic dataset collection relevant to embryonic development associated with in vitro fertilization in healthy individuals and patients with polycystic ovary syndrome
title_full_unstemmed ­A curated transcriptomic dataset collection relevant to embryonic development associated with in vitro fertilization in healthy individuals and patients with polycystic ovary syndrome
title_short ­A curated transcriptomic dataset collection relevant to embryonic development associated with in vitro fertilization in healthy individuals and patients with polycystic ovary syndrome
title_sort ­a curated transcriptomic dataset collection relevant to embryonic development associated with in vitro fertilization in healthy individuals and patients with polycystic ovary syndrome
topic Data Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5365227/
https://www.ncbi.nlm.nih.gov/pubmed/28413616
http://dx.doi.org/10.12688/f1000research.10877.1
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