Publication Details

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Title (Primary) uap: reproducible and robust HTS data analysis
Author Kämpf, C.; Specht, M.; Scholz, A.; Puppel, S.-H.; Doose, G.; Reiche, K.; Schor, J.; Hackermüller, J.;
Journal BMC Bioinformatics
Year 2019
Department MOLSYB;
Volume 20
Language englisch;
POF III (all) T42; F11;
Data links https://github.com/yigbt/uap
Supplements https://static-content.springer.com/esm/art%3A10.1186%2Fs12859-019-3219-1/MediaObjects/12859_2019_3219_MOESM1_ESM.pdf
Abstract Background

A lack of reproducibility has been repeatedly criticized in computational research. High throughput sequencing (HTS) data analysis is a complex multi-step process. For most of the steps a range of bioinformatic tools is available and for most tools manifold parameters need to be set. Due to this complexity, HTS data analysis is particularly prone to reproducibility and consistency issues. We have defined four criteria that in our opinion ensure a minimal degree of reproducible research for HTS data analysis. A series of workflow management systems is available for assisting complex multi-step data analyses. However, to the best of our knowledge, none of the currently available work flow management systems satisfies all four criteria for reproducible HTS analysis.

Results

Here we present uap, a workflow management system dedicated to robust, consistent, and reproducible HTS data analysis. uap is optimized for the application to omics data, but can be easily extended to other complex analyses. It is available under the GNU GPL v3 license at https://github.com/yigbt/uap.

Conclusions

uap is a freely available tool that enables researchers to easily adhere to reproducible research principles for HTS data analyses.
ID 22544
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=22544
Kämpf, C., Specht, M., Scholz, A., Puppel, S.-H., Doose, G., Reiche, K., Schor, J., Hackermüller, J. (2019):
uap: reproducible and robust HTS data analysis
BMC Bioinformatics 20 , art. 664