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Bioinformatics analysis

JC José F. Català-Senent
MH Marta R. Hidalgo
MB Marina Berenguer
GP Gopanandan Parthasarathy
HM Harmeet Malhi
PM Pablo Malmierca-Merlo
MI María de la Iglesia-Vayá
FG Francisco García-García
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The same three-step transcriptomic analysis strategy was applied to each separate study: (i) data acquisition and preprocessing, (ii) differential gene expression and functional enrichment analysis, and (iii) differential pathway activation and functional analysis. The functional results of all studies were integrated using meta-analytical techniques (Fig. ​(Fig.1).1). Bioinformatics analysis was carried out using the programming language R 3.6.0 [12]; information regarding the packages used and their version numbers are provided in the supplementary material.

Data analysis workflow

Copyright and License information: The Author(s) ©2021
Open AccessThis 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/. 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 in a credit line to the data.

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