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Bioinformatics for wet-lab scientists: practical application in sequencing analysis

BACKGROUND: Genomics data is available to the scientific community after publication of research projects and can be investigated for a multitude of research questions. However, in many cases deposited data is only assessed and used for the initial publication, resulting in valuable resources not be...

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Autores principales: Laub, Vera, Devraj, Kavi, Elias, Lena, Schulte, Dorothea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10326960/
https://www.ncbi.nlm.nih.gov/pubmed/37420172
http://dx.doi.org/10.1186/s12864-023-09454-7
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author Laub, Vera
Devraj, Kavi
Elias, Lena
Schulte, Dorothea
author_facet Laub, Vera
Devraj, Kavi
Elias, Lena
Schulte, Dorothea
author_sort Laub, Vera
collection PubMed
description BACKGROUND: Genomics data is available to the scientific community after publication of research projects and can be investigated for a multitude of research questions. However, in many cases deposited data is only assessed and used for the initial publication, resulting in valuable resources not being exploited to their full depth. MAIN: A likely reason for this is that many wetlab-based researchers are not formally trained to apply bioinformatic tools and may therefore assume that they lack the necessary experience to do so themselves. In this article, we present a series of freely available, predominantly web-based platforms and bioinformatic tools that can be combined in analysis pipelines to interrogate different types of next-generation sequencing data. Additionally to the presented exemplary route, we also list a number of alternative tools that can be combined in a mix-and-match fashion. We place special emphasis on tools that can be followed and used correctly without extensive prior knowledge in programming. Such analysis pipelines can be applied to existing data downloaded from the public domain or be compared to the results of own experiments. CONCLUSION: Integrating transcription factor binding to chromatin (ChIP-seq) with transcriptional output (RNA-seq) and chromatin accessibility (ATAC-seq) can not only assist to form a deeper understanding of the molecular interactions underlying transcriptional regulation but will also help establishing new hypotheses and pre-testing them in silico.
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spelling pubmed-103269602023-07-08 Bioinformatics for wet-lab scientists: practical application in sequencing analysis Laub, Vera Devraj, Kavi Elias, Lena Schulte, Dorothea BMC Genomics Research BACKGROUND: Genomics data is available to the scientific community after publication of research projects and can be investigated for a multitude of research questions. However, in many cases deposited data is only assessed and used for the initial publication, resulting in valuable resources not being exploited to their full depth. MAIN: A likely reason for this is that many wetlab-based researchers are not formally trained to apply bioinformatic tools and may therefore assume that they lack the necessary experience to do so themselves. In this article, we present a series of freely available, predominantly web-based platforms and bioinformatic tools that can be combined in analysis pipelines to interrogate different types of next-generation sequencing data. Additionally to the presented exemplary route, we also list a number of alternative tools that can be combined in a mix-and-match fashion. We place special emphasis on tools that can be followed and used correctly without extensive prior knowledge in programming. Such analysis pipelines can be applied to existing data downloaded from the public domain or be compared to the results of own experiments. CONCLUSION: Integrating transcription factor binding to chromatin (ChIP-seq) with transcriptional output (RNA-seq) and chromatin accessibility (ATAC-seq) can not only assist to form a deeper understanding of the molecular interactions underlying transcriptional regulation but will also help establishing new hypotheses and pre-testing them in silico. BioMed Central 2023-07-07 /pmc/articles/PMC10326960/ /pubmed/37420172 http://dx.doi.org/10.1186/s12864-023-09454-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Laub, Vera
Devraj, Kavi
Elias, Lena
Schulte, Dorothea
Bioinformatics for wet-lab scientists: practical application in sequencing analysis
title Bioinformatics for wet-lab scientists: practical application in sequencing analysis
title_full Bioinformatics for wet-lab scientists: practical application in sequencing analysis
title_fullStr Bioinformatics for wet-lab scientists: practical application in sequencing analysis
title_full_unstemmed Bioinformatics for wet-lab scientists: practical application in sequencing analysis
title_short Bioinformatics for wet-lab scientists: practical application in sequencing analysis
title_sort bioinformatics for wet-lab scientists: practical application in sequencing analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10326960/
https://www.ncbi.nlm.nih.gov/pubmed/37420172
http://dx.doi.org/10.1186/s12864-023-09454-7
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