ArticleMethods in molecular biology (Clifton, N.J.)2024
Bioinformatics Methods for Transcriptome Analysis on Teratogenesis Testing.
Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Identification of key oxidative phosphorylation-related genes in systemic lupus erythematosus based on transcriptomics and bioinformatics analysis.Journal of translational autoimmunity · 2025Article
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Authors and funding
5 authors at 2 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
Teratogenesis testing can be challenging due to the limitations of both in vitro and in vivo models. Test-systems, based especially on human embryonic cells, have been helping to overcome the difficulties when allied to omics strategies, such as transcriptomics. In these test-systems, cells exposed to different compounds are then analyzed in microarray or RNA-seq platforms regarding the impacts of the potential teratogens in the gene expression. Nevertheless, microarray and RNA-seq dataset processing requires computational resources and bioinformatics knowledge. Here, a pipeline for microarray and RNA-seq processing is presented, aiming to help researchers from any field to interpret the main transcriptome results, such as differential gene expression, enrichment analysis, and statistical interpretation. This chapter also discusses the main difficulties that can be encountered in a transcriptome analysis and the better alternatives to overcome these issues, describing both programming codes and user-friendly tools. Finally, specific issues in the teratogenesis field, such as time-course analysis, are also described, demonstrating how the pipeline can be applied in these studies.
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Registered trials
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