Analysis workflow of publicly available RNA-sequencing datasets

Analysis workflow of publicly available RNA-sequencing datasets

Summary: Differential gene expression analysis is widely used to study changes in gene expression profiles between two or more groups of samples (e.g., physiological versus pathological conditions, pre-treatment versus post-treatment, and infected versus non-infected tissues). This protocol aims to...

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Main Authors: Pablo Sanchis, Rosario Lavignolle, Mercedes Abbate, Sofía Lage-Vickers, Elba Vazquez, Javier Cotignola, Juan Bizzotto, Geraldine Gueron
Format: Article
Language:English
Published: Elsevier 2021-06-01
Series:STAR Protocols
Subjects:
Bioinformatics
RNAseq
Online Access:http://www.sciencedirect.com/science/article/pii/S2666166721001854
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spelling doaj-67aaf13c93084058b389627403a7fec62021-06-21T04:25:20ZengElsevierSTAR Protocols2666-16672021-06-0122100478Analysis workflow of publicly available RNA-sequencing datasetsPablo Sanchis0Rosario Lavignolle1Mercedes Abbate2Sofía Lage-Vickers3Elba Vazquez4Javier Cotignola5Juan Bizzotto6Geraldine Gueron7Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Buenos Aires C1428EGA, Argentina; CONICET - Universidad de Buenos Aires, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Buenos Aires C1428EGA, Argentina; Corresponding authorUniversidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Buenos Aires C1428EGA, Argentina; CONICET - Universidad de Buenos Aires, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Buenos Aires C1428EGA, Argentina; Corresponding authorUniversidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Buenos Aires C1428EGA, Argentina; CONICET - Universidad de Buenos Aires, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Buenos Aires C1428EGA, ArgentinaUniversidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Buenos Aires C1428EGA, Argentina; CONICET - Universidad de Buenos Aires, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Buenos Aires C1428EGA, ArgentinaUniversidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Buenos Aires C1428EGA, Argentina; CONICET - Universidad de Buenos Aires, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Buenos Aires C1428EGA, ArgentinaUniversidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Buenos Aires C1428EGA, Argentina; CONICET - Universidad de Buenos Aires, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Buenos Aires C1428EGA, ArgentinaUniversidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Buenos Aires C1428EGA, Argentina; CONICET - Universidad de Buenos Aires, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Buenos Aires C1428EGA, ArgentinaUniversidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Buenos Aires C1428EGA, Argentina; CONICET - Universidad de Buenos Aires, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Buenos Aires C1428EGA, Argentina; Corresponding authorSummary: Differential gene expression analysis is widely used to study changes in gene expression profiles between two or more groups of samples (e.g., physiological versus pathological conditions, pre-treatment versus post-treatment, and infected versus non-infected tissues). This protocol aims to identify gene expression changes in a pre-selected set of genes associated with severe acute respiratory syndrome coronavirus 2 viral infection and host cell antiviral response, as well as subsequent gene expression association with phenotypic features using samples deposited in public repositories.For complete details on the use and outcome of this informatics analysis, please refer to Bizzotto et al. (2020).http://www.sciencedirect.com/science/article/pii/S2666166721001854BioinformaticsRNAseq
collection DOAJ
language English
format Article
sources DOAJ
author Pablo Sanchis
Rosario Lavignolle
Mercedes Abbate
Sofía Lage-Vickers
Elba Vazquez
Javier Cotignola
Juan Bizzotto
Geraldine Gueron
spellingShingle Pablo Sanchis
Rosario Lavignolle
Mercedes Abbate
Sofía Lage-Vickers
Elba Vazquez
Javier Cotignola
Juan Bizzotto
Geraldine Gueron
Analysis workflow of publicly available RNA-sequencing datasets
STAR Protocols
Bioinformatics
RNAseq
author_facet Pablo Sanchis
Rosario Lavignolle
Mercedes Abbate
Sofía Lage-Vickers
Elba Vazquez
Javier Cotignola
Juan Bizzotto
Geraldine Gueron
author_sort Pablo Sanchis
title Analysis workflow of publicly available RNA-sequencing datasets
title_short Analysis workflow of publicly available RNA-sequencing datasets
title_full Analysis workflow of publicly available RNA-sequencing datasets
title_fullStr Analysis workflow of publicly available RNA-sequencing datasets
title_full_unstemmed Analysis workflow of publicly available RNA-sequencing datasets
title_sort analysis workflow of publicly available rna-sequencing datasets
publisher Elsevier
series STAR Protocols
issn 2666-1667
publishDate 2021-06-01
description Summary: Differential gene expression analysis is widely used to study changes in gene expression profiles between two or more groups of samples (e.g., physiological versus pathological conditions, pre-treatment versus post-treatment, and infected versus non-infected tissues). This protocol aims to identify gene expression changes in a pre-selected set of genes associated with severe acute respiratory syndrome coronavirus 2 viral infection and host cell antiviral response, as well as subsequent gene expression association with phenotypic features using samples deposited in public repositories.For complete details on the use and outcome of this informatics analysis, please refer to Bizzotto et al. (2020).
topic Bioinformatics
RNAseq
url http://www.sciencedirect.com/science/article/pii/S2666166721001854
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