Cargando…

STATegra EMS: an Experiment Management System for complex next-generation omics experiments

High-throughput sequencing assays are now routinely used to study different aspects of genome organization. As decreasing costs and widespread availability of sequencing enable more laboratories to use sequencing assays in their research projects, the number of samples and replicates in these experi...

Descripción completa

Detalles Bibliográficos
Autores principales: Hernández-de-Diego, Rafael, Boix-Chova, Noemi, Gómez-Cabrero, David, Tegner, Jesper, Abugessaisa, Imad, Conesa, Ana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4101697/
https://www.ncbi.nlm.nih.gov/pubmed/25033091
http://dx.doi.org/10.1186/1752-0509-8-S2-S9
_version_ 1782480936271609856
author Hernández-de-Diego, Rafael
Boix-Chova, Noemi
Gómez-Cabrero, David
Tegner, Jesper
Abugessaisa, Imad
Conesa, Ana
author_facet Hernández-de-Diego, Rafael
Boix-Chova, Noemi
Gómez-Cabrero, David
Tegner, Jesper
Abugessaisa, Imad
Conesa, Ana
author_sort Hernández-de-Diego, Rafael
collection PubMed
description High-throughput sequencing assays are now routinely used to study different aspects of genome organization. As decreasing costs and widespread availability of sequencing enable more laboratories to use sequencing assays in their research projects, the number of samples and replicates in these experiments can quickly grow to several dozens of samples and thus require standardized annotation, storage and management of preprocessing steps. As a part of the STATegra project, we have developed an Experiment Management System (EMS) for high throughput omics data that supports different types of sequencing-based assays such as RNA-seq, ChIP-seq, Methyl-seq, etc, as well as proteomics and metabolomics data. The STATegra EMS provides metadata annotation of experimental design, samples and processing pipelines, as well as storage of different types of data files, from raw data to ready-to-use measurements. The system has been developed to provide research laboratories with a freely-available, integrated system that offers a simple and effective way for experiment annotation and tracking of analysis procedures.
format Online
Article
Text
id pubmed-4101697
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-41016972014-07-18 STATegra EMS: an Experiment Management System for complex next-generation omics experiments Hernández-de-Diego, Rafael Boix-Chova, Noemi Gómez-Cabrero, David Tegner, Jesper Abugessaisa, Imad Conesa, Ana BMC Syst Biol Research High-throughput sequencing assays are now routinely used to study different aspects of genome organization. As decreasing costs and widespread availability of sequencing enable more laboratories to use sequencing assays in their research projects, the number of samples and replicates in these experiments can quickly grow to several dozens of samples and thus require standardized annotation, storage and management of preprocessing steps. As a part of the STATegra project, we have developed an Experiment Management System (EMS) for high throughput omics data that supports different types of sequencing-based assays such as RNA-seq, ChIP-seq, Methyl-seq, etc, as well as proteomics and metabolomics data. The STATegra EMS provides metadata annotation of experimental design, samples and processing pipelines, as well as storage of different types of data files, from raw data to ready-to-use measurements. The system has been developed to provide research laboratories with a freely-available, integrated system that offers a simple and effective way for experiment annotation and tracking of analysis procedures. BioMed Central 2014-03-13 /pmc/articles/PMC4101697/ /pubmed/25033091 http://dx.doi.org/10.1186/1752-0509-8-S2-S9 Text en Copyright © 2014 Hernández-de-Diego et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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 Research
Hernández-de-Diego, Rafael
Boix-Chova, Noemi
Gómez-Cabrero, David
Tegner, Jesper
Abugessaisa, Imad
Conesa, Ana
STATegra EMS: an Experiment Management System for complex next-generation omics experiments
title STATegra EMS: an Experiment Management System for complex next-generation omics experiments
title_full STATegra EMS: an Experiment Management System for complex next-generation omics experiments
title_fullStr STATegra EMS: an Experiment Management System for complex next-generation omics experiments
title_full_unstemmed STATegra EMS: an Experiment Management System for complex next-generation omics experiments
title_short STATegra EMS: an Experiment Management System for complex next-generation omics experiments
title_sort stategra ems: an experiment management system for complex next-generation omics experiments
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4101697/
https://www.ncbi.nlm.nih.gov/pubmed/25033091
http://dx.doi.org/10.1186/1752-0509-8-S2-S9
work_keys_str_mv AT hernandezdediegorafael stategraemsanexperimentmanagementsystemforcomplexnextgenerationomicsexperiments
AT boixchovanoemi stategraemsanexperimentmanagementsystemforcomplexnextgenerationomicsexperiments
AT gomezcabrerodavid stategraemsanexperimentmanagementsystemforcomplexnextgenerationomicsexperiments
AT tegnerjesper stategraemsanexperimentmanagementsystemforcomplexnextgenerationomicsexperiments
AT abugessaisaimad stategraemsanexperimentmanagementsystemforcomplexnextgenerationomicsexperiments
AT conesaana stategraemsanexperimentmanagementsystemforcomplexnextgenerationomicsexperiments