Abstract
BackgroundA 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.ResultsHere 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.Conclusionsuap is a freely available tool that enables researchers to easily adhere to reproducible research principles for HTS data analyses.
Highlights
A lack of reproducibility has been repeatedly criticized in computational research
Background generation or high throughput sequencing (HTS) methods that rely on massively parallel DNA sequencing have opened a new era of molecular life sciences
We provide complete workflows for handling genomic data and analyzing RNA-Seq and Chromatin Immuno-Precipitation DNA-Sequencing (ChIP-seq) data, which can be used as templates that allow for easy customization
Summary
A lack of reproducibility has been repeatedly criticized in computational research. High throughput sequencing (HTS) data analysis is a complex multi-step process. A minimal degree of reproducible research in managing HTS data analyses requires a tool which ensures that (i) the dependencies between analysis steps and intermediate results are correctly maintained, (ii) analysis steps are successfully completed prior to execution of subsequent steps, (iii) all tools, their versions and full parameter sets (including standard parameters which are usually not set when starting the tool from the commandline) are logged, (iv), the consistency between the code defining the analysis and the currently available results is ensured. Additional file 1: Figure S1 shows the DAG including its runs rendered by uap based on the configuration file for the analysis of a published data set.
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