Survival analysis tools in genomics research

There is an increasing demand to determine the clinical implication of experimental findings in molecular biomedical research. Survival (or failure time) analysis methodologies have been adapted to the analysis of genomics data to link molecular information with clinical outcomes of interest. Genome...

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Detalles Bibliográficos
Autores principales: Chen, Xintong, Sun, Xiaochen, Hoshida, Yujin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Software Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4246473/
https://www.ncbi.nlm.nih.gov/pubmed/25421963
http://dx.doi.org/10.1186/s40246-014-0021-z
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author Chen, Xintong
Sun, Xiaochen
Hoshida, Yujin
author_facet Chen, Xintong
Sun, Xiaochen
Hoshida, Yujin
author_sort Chen, Xintong
collection PubMed
description There is an increasing demand to determine the clinical implication of experimental findings in molecular biomedical research. Survival (or failure time) analysis methodologies have been adapted to the analysis of genomics data to link molecular information with clinical outcomes of interest. Genome-wide molecular profiles have served as sources for discovery of predictive/prognostic biomarkers as well as therapeutic targets in the past decade. In this review, we overview currently available software, web applications, and databases specifically developed for survival analysis in genomics research and discuss issues in assessing clinical utility of molecular features derived from genomic profiling.
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spelling pubmed-42464732014-11-29 Survival analysis tools in genomics research Chen, Xintong Sun, Xiaochen Hoshida, Yujin Hum Genomics Software Review There is an increasing demand to determine the clinical implication of experimental findings in molecular biomedical research. Survival (or failure time) analysis methodologies have been adapted to the analysis of genomics data to link molecular information with clinical outcomes of interest. Genome-wide molecular profiles have served as sources for discovery of predictive/prognostic biomarkers as well as therapeutic targets in the past decade. In this review, we overview currently available software, web applications, and databases specifically developed for survival analysis in genomics research and discuss issues in assessing clinical utility of molecular features derived from genomic profiling. BioMed Central 2014-11-25 /pmc/articles/PMC4246473/ /pubmed/25421963 http://dx.doi.org/10.1186/s40246-014-0021-z Text en © Chen et al.; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software Review
Chen, Xintong
Sun, Xiaochen
Hoshida, Yujin
Survival analysis tools in genomics research
title Survival analysis tools in genomics research
title_full Survival analysis tools in genomics research
title_fullStr Survival analysis tools in genomics research
title_full_unstemmed Survival analysis tools in genomics research
title_short Survival analysis tools in genomics research
title_sort survival analysis tools in genomics research
topic Software Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4246473/
https://www.ncbi.nlm.nih.gov/pubmed/25421963
http://dx.doi.org/10.1186/s40246-014-0021-z
work_keys_str_mv AT chenxintong survivalanalysistoolsingenomicsresearch
AT sunxiaochen survivalanalysistoolsingenomicsresearch
AT hoshidayujin survivalanalysistoolsingenomicsresearch

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