2023
DOI: 10.1101/2023.07.12.548663
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reanalyzerGSE: tackling the everlasting lack of reproducibility and reanalyses in transcriptomics

José L Ruiz,
Laura C Terrón-Camero,
Julia Castillo-González
et al.

Abstract: In the current context of transcriptomics democratization, there is an unprecedented surge in the number of studies and datasets. However, advances are hampered by aspects such as the reproducibility crisis, and lack of standardization, in particular with scarce reanalyses of secondary data. reanalyzerGSE, is a user-friendly pipeline that aims to be an all-in-one automatic solution for locally available transcriptomic data and those found in public repositories, thereby encouraging data reuse. With its modular… Show more

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Cited by 2 publications
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“…We obtained a mean GC content of 51.3%, and 40,407,022 paired-end reads and > 28,000 transcripts on average. Considering the low levels of cortistatin expression, we have implemented the reanalyzerGSE software [ 22 , 23 ] for transcriptomic studies. This pipeline was implemented in the RNA-seq analysis to identify differentially expressed genes (DEGs) and to prevent the exclusion of low expressed genes with potential biological relevance (see details in Additional file 1 ).…”
Section: Methodsmentioning
confidence: 99%
“…We obtained a mean GC content of 51.3%, and 40,407,022 paired-end reads and > 28,000 transcripts on average. Considering the low levels of cortistatin expression, we have implemented the reanalyzerGSE software [ 22 , 23 ] for transcriptomic studies. This pipeline was implemented in the RNA-seq analysis to identify differentially expressed genes (DEGs) and to prevent the exclusion of low expressed genes with potential biological relevance (see details in Additional file 1 ).…”
Section: Methodsmentioning
confidence: 99%