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OSlms: A Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma

The availability of transcriptome data and clinical annotation offers the opportunity to identify prognosis biomarkers in cancer. However, efficient online prognosis analysis tools are still lacking. Herein, we developed a user-friendly web server, namely Online consensus Survival analysis of leiomy...

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Detalles Bibliográficos
Autores principales: Wang, Qiang, Xie, Longxiang, Dang, Yifang, Sun, Xiaoxiao, Xie, Tiantian, Guo, Jinshuai, Han, Yali, Yan, Zhongyi, Zhu, Wan, Wang, Yunlong, Li, Wei, Guo, Xiangqian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449415/
https://www.ncbi.nlm.nih.gov/pubmed/30984618
http://dx.doi.org/10.3389/fonc.2019.00190
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author Wang, Qiang
Xie, Longxiang
Dang, Yifang
Sun, Xiaoxiao
Xie, Tiantian
Guo, Jinshuai
Han, Yali
Yan, Zhongyi
Zhu, Wan
Wang, Yunlong
Li, Wei
Guo, Xiangqian
author_facet Wang, Qiang
Xie, Longxiang
Dang, Yifang
Sun, Xiaoxiao
Xie, Tiantian
Guo, Jinshuai
Han, Yali
Yan, Zhongyi
Zhu, Wan
Wang, Yunlong
Li, Wei
Guo, Xiangqian
author_sort Wang, Qiang
collection PubMed
description The availability of transcriptome data and clinical annotation offers the opportunity to identify prognosis biomarkers in cancer. However, efficient online prognosis analysis tools are still lacking. Herein, we developed a user-friendly web server, namely Online consensus Survival analysis of leiomyosarcoma (OSlms), to centralize published gene expression data and clinical datasets of leiomyosarcoma (LMS) patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). OSlms comprises of a total of 268 samples from three independent datasets, and employs the Kaplan Meier survival plot with hazard ratio (HR) and log rank test to estimate the prognostic potency of genes of interests for LMS patients. Using OSlms, clinicians and basic researchers could determine the prognostic significance of genes of interests and get opportunities to identify novel potential important molecules for LMS. OSlms is free and publicly accessible at http://bioinfo.henu.edu.cn/LMS/LMSList.jsp.
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spelling pubmed-64494152019-04-12 OSlms: A Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma Wang, Qiang Xie, Longxiang Dang, Yifang Sun, Xiaoxiao Xie, Tiantian Guo, Jinshuai Han, Yali Yan, Zhongyi Zhu, Wan Wang, Yunlong Li, Wei Guo, Xiangqian Front Oncol Oncology The availability of transcriptome data and clinical annotation offers the opportunity to identify prognosis biomarkers in cancer. However, efficient online prognosis analysis tools are still lacking. Herein, we developed a user-friendly web server, namely Online consensus Survival analysis of leiomyosarcoma (OSlms), to centralize published gene expression data and clinical datasets of leiomyosarcoma (LMS) patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). OSlms comprises of a total of 268 samples from three independent datasets, and employs the Kaplan Meier survival plot with hazard ratio (HR) and log rank test to estimate the prognostic potency of genes of interests for LMS patients. Using OSlms, clinicians and basic researchers could determine the prognostic significance of genes of interests and get opportunities to identify novel potential important molecules for LMS. OSlms is free and publicly accessible at http://bioinfo.henu.edu.cn/LMS/LMSList.jsp. Frontiers Media S.A. 2019-03-29 /pmc/articles/PMC6449415/ /pubmed/30984618 http://dx.doi.org/10.3389/fonc.2019.00190 Text en Copyright © 2019 Wang, Xie, Dang, Sun, Xie, Guo, Han, Yan, Zhu, Wang, Li and Guo. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Wang, Qiang
Xie, Longxiang
Dang, Yifang
Sun, Xiaoxiao
Xie, Tiantian
Guo, Jinshuai
Han, Yali
Yan, Zhongyi
Zhu, Wan
Wang, Yunlong
Li, Wei
Guo, Xiangqian
OSlms: A Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma
title OSlms: A Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma
title_full OSlms: A Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma
title_fullStr OSlms: A Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma
title_full_unstemmed OSlms: A Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma
title_short OSlms: A Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma
title_sort oslms: a web server to evaluate the prognostic value of genes in leiomyosarcoma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449415/
https://www.ncbi.nlm.nih.gov/pubmed/30984618
http://dx.doi.org/10.3389/fonc.2019.00190
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