Cargando…
GeneTrail: A Framework for the Analysis of High-Throughput Profiles
Experimental high-throughput techniques, like next-generation sequencing or microarrays, are nowadays routinely applied to create detailed molecular profiles of cells. In general, these platforms generate high-dimensional and noisy data sets. For their analysis, powerful bioinformatics tools are req...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481803/ https://www.ncbi.nlm.nih.gov/pubmed/34604304 http://dx.doi.org/10.3389/fmolb.2021.716544 |
_version_ | 1784576761307070464 |
---|---|
author | Gerstner, Nico Kehl, Tim Lenhof, Kerstin Eckhart, Lea Schneider, Lara Stöckel, Daniel Backes, Christina Meese, Eckart Keller, Andreas Lenhof, Hans-Peter |
author_facet | Gerstner, Nico Kehl, Tim Lenhof, Kerstin Eckhart, Lea Schneider, Lara Stöckel, Daniel Backes, Christina Meese, Eckart Keller, Andreas Lenhof, Hans-Peter |
author_sort | Gerstner, Nico |
collection | PubMed |
description | Experimental high-throughput techniques, like next-generation sequencing or microarrays, are nowadays routinely applied to create detailed molecular profiles of cells. In general, these platforms generate high-dimensional and noisy data sets. For their analysis, powerful bioinformatics tools are required to gain novel insights into the biological processes under investigation. Here, we present an overview of the GeneTrail tool suite that offers rich functionality for the analysis and visualization of (epi-)genomic, transcriptomic, miRNomic, and proteomic profiles. Our framework enables the analysis of standard bulk, time-series, and single-cell measurements and includes various state-of-the-art methods to identify potentially deregulated biological processes and to detect driving factors within those deregulated processes. We highlight the capabilities of our web service with an analysis of a single-cell COVID-19 data set that demonstrates its potential for uncovering complex molecular mechanisms. GeneTrail can be accessed freely and without login requirements at http://genetrail.bioinf.uni-sb.de. |
format | Online Article Text |
id | pubmed-8481803 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84818032021-10-01 GeneTrail: A Framework for the Analysis of High-Throughput Profiles Gerstner, Nico Kehl, Tim Lenhof, Kerstin Eckhart, Lea Schneider, Lara Stöckel, Daniel Backes, Christina Meese, Eckart Keller, Andreas Lenhof, Hans-Peter Front Mol Biosci Molecular Biosciences Experimental high-throughput techniques, like next-generation sequencing or microarrays, are nowadays routinely applied to create detailed molecular profiles of cells. In general, these platforms generate high-dimensional and noisy data sets. For their analysis, powerful bioinformatics tools are required to gain novel insights into the biological processes under investigation. Here, we present an overview of the GeneTrail tool suite that offers rich functionality for the analysis and visualization of (epi-)genomic, transcriptomic, miRNomic, and proteomic profiles. Our framework enables the analysis of standard bulk, time-series, and single-cell measurements and includes various state-of-the-art methods to identify potentially deregulated biological processes and to detect driving factors within those deregulated processes. We highlight the capabilities of our web service with an analysis of a single-cell COVID-19 data set that demonstrates its potential for uncovering complex molecular mechanisms. GeneTrail can be accessed freely and without login requirements at http://genetrail.bioinf.uni-sb.de. Frontiers Media S.A. 2021-09-16 /pmc/articles/PMC8481803/ /pubmed/34604304 http://dx.doi.org/10.3389/fmolb.2021.716544 Text en Copyright © 2021 Gerstner, Kehl, Lenhof, Eckhart, Schneider, Stöckel, Backes, Meese, Keller and Lenhof. https://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 | Molecular Biosciences Gerstner, Nico Kehl, Tim Lenhof, Kerstin Eckhart, Lea Schneider, Lara Stöckel, Daniel Backes, Christina Meese, Eckart Keller, Andreas Lenhof, Hans-Peter GeneTrail: A Framework for the Analysis of High-Throughput Profiles |
title | GeneTrail: A Framework for the Analysis of High-Throughput Profiles |
title_full | GeneTrail: A Framework for the Analysis of High-Throughput Profiles |
title_fullStr | GeneTrail: A Framework for the Analysis of High-Throughput Profiles |
title_full_unstemmed | GeneTrail: A Framework for the Analysis of High-Throughput Profiles |
title_short | GeneTrail: A Framework for the Analysis of High-Throughput Profiles |
title_sort | genetrail: a framework for the analysis of high-throughput profiles |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481803/ https://www.ncbi.nlm.nih.gov/pubmed/34604304 http://dx.doi.org/10.3389/fmolb.2021.716544 |
work_keys_str_mv | AT gerstnernico genetrailaframeworkfortheanalysisofhighthroughputprofiles AT kehltim genetrailaframeworkfortheanalysisofhighthroughputprofiles AT lenhofkerstin genetrailaframeworkfortheanalysisofhighthroughputprofiles AT eckhartlea genetrailaframeworkfortheanalysisofhighthroughputprofiles AT schneiderlara genetrailaframeworkfortheanalysisofhighthroughputprofiles AT stockeldaniel genetrailaframeworkfortheanalysisofhighthroughputprofiles AT backeschristina genetrailaframeworkfortheanalysisofhighthroughputprofiles AT meeseeckart genetrailaframeworkfortheanalysisofhighthroughputprofiles AT kellerandreas genetrailaframeworkfortheanalysisofhighthroughputprofiles AT lenhofhanspeter genetrailaframeworkfortheanalysisofhighthroughputprofiles |