Strategic roadmap for FAIR-compliant transcriptomic workflows: from technical challenges to bioinformatics democratization
- 1Unidad Universitaria de Secuenciación Masiva y Bioinformática, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, Mexico
- 2Instituto de Ciencias Aplicadas y Tecnología, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
Abstract
This article draws on the authors’ more than 17 years of experience in transcriptomic research, beginning with the introduction of high-throughput sequencing in Mexico in 2009. Here, we provide a critical review of bioinformatics pipelines for different RNA classes, ranging from small RNAs to long non-coding RNAs. Our analysis encompasses a range of scenarios, from de novo transcriptome assembly for organisms lacking a closely related and adequately annotated reference genome to differential expression analysis based on a well-annotated reference genome. By providing a comprehensive overview of the workflow, from RNA extraction and high-throughput sequencing to quality control and data preprocessing, we offer a practical framework to help researchers select tools that are appropriate for their biological questions and experimental contexts. We further examine advanced strategies for transcriptome assembly, sequence alignment, and transcript abundance quantification. Finally, we discuss differential expression and functional enrichment analyses, emphasizing the importance of standardized, FAIR-compliant workflows and the democratization of transcriptomic analysis in promoting inclusive and reproducible genomic research. We also present IDEAMEX, a web-based platform designed to democratize transcriptomic analysis by reducing technical and systemic barriers and promoting equitable access to robust analytical tools, particularly for researchers in resource-limited settings who may not have advanced programming skills.
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BibTeX
@article{jacinto2026strategic,
title = {{Strategic roadmap for FAIR-compliant transcriptomic workflows: from technical challenges to bioinformatics democratization}},
author = {Verónica Jiménez Jacinto and Leticia Vega-Alvarado},
journal = {Frontiers in Bioinformatics},
year = {2026},
month = oct,
doi = {10.3389/fbinf.2026.1882808},
url = {https://doi.org/10.3389/fbinf.2026.1882808},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Strategic roadmap for FAIR-compliant transcriptomic workflows: from technical challenges to bioinformatics democratization
AU - Verónica Jiménez Jacinto
AU - Leticia Vega-Alvarado
PY - 2026
DA - 2026/10/12
JO - Frontiers in Bioinformatics
DO - 10.3389/fbinf.2026.1882808
UR - https://doi.org/10.3389/fbinf.2026.1882808
AB - This article draws on the authors’ more than 17 years of experience in transcriptomic research, beginning with the introduction of high-throughput sequencing in Mexico in 2009. Here, we provide a critical review of bioinformatics pipelines for different RNA classes, ranging from small RNAs to long non-coding RNAs. Our analysis encompasses a range of scenarios, from de novo transcriptome assembly for organisms lacking a closely related and adequately annotated reference genome to differential expression analysis based on a well-annotated reference genome. By providing a comprehensive overview of the workflow, from RNA extraction and high-throughput sequencing to quality control and data preprocessing, we offer a practical framework to help researchers select tools that are appropriate for their biological questions and experimental contexts. We further examine advanced strategies for transcriptome assembly, sequence alignment, and transcript abundance quantification. Finally, we discuss differential expression and functional enrichment analyses, emphasizing the importance of standardized, FAIR-compliant workflows and the democratization of transcriptomic analysis in promoting inclusive and reproducible genomic research. We also present IDEAMEX, a web-based platform designed to democratize transcriptomic analysis by reducing technical and systemic barriers and promoting equitable access to robust analytical tools, particularly for researchers in resource-limited settings who may not have advanced programming skills.
SN - 2673-7647
ER -