BARRA:CuRDa

BARRA:CuRDa

BARRA:CuRDa

A Curated RNA-seq Database for Cancer Research

RNA-seq is gradually becoming the dominating technique employed to access the global gene expression in biological samples, allowing more flexible protocols and robust analysis. However, the nature of RNA-seq results im-pose new data-handling challenges when it comes to computational analysis. With the increasing employment of machine learning techniques in biomedical sciences, databases that could provide curated datasets treated with state-of-the-art approaches already adapted to machine learning protocols become essential for testing new algorithms.

BARRA:CuRDa is composed of 17 handpicked RNA-seq datasets for Homo sapiens gathered from the Gene Expression Omnibus (GEO), using rigorous filtering criteria. All datasets were individually submitted to sample quality analysis, removal of low-quality bases, artifacts from the experimental process, removal of ribosomal RNA, and transcript level abundance. Moreover, like its sister database, all datasets were tested using analyses destined to provide a base knowledge of each dataset's characteristics, with the addition of new metrics.

How to CIte

If you use BARRA:CuRDa in a scientific publication, we would appreciate citations to the following paper:

BibTeX

@article{barracurda:2021,
    author = {Feltes, B. and Poloni, J. and Dorn, M.},
    doi = {10.1089/cmb.2020.0463},
    journal = {Journal of Computational Biology},
    number = {9},
    pages = {931--944},
    title = {{Benchmarking and Testing Machine Learning Approaches with BARRA:CuRDa, a Curated RNA-Seq Database for Cancer Research}},
    url = {https://doi.org/10.1089/cmb.2020.0463},
    volume = {28},
    year = {2021}
}

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