The content of this report is from the preprint of a

Applications Note by Nils Gehlenborg, Michael S. Noble, Gad Getz, Lynda Chin
and Peter J. Park describing the Nozzle package. This Nozzle version of the preprint
was created to demonstrate features of the Nozzle package. Please view the final
article on the

We have developed Nozzle, an R package that provides
an API to generate HTML reports with dynamic user interface elements. Nozzle
was designed to facilitate summarization and rapid browsing of complex results
in data analysis pipelines where multiple analyses are performed frequently on
big data sets. The package can be applied to any project where user-friendly
reports need to be created.

. Examples and
additional materials are available at

Supplementary data are available at
Bioinformatics online.

Due to the increasing size and complexity of biological data, a considerable 
portion of bioinformatics analyses are implemented as (semi-)automated
pipelines. The main task of these pipelines is to control the flow of 
large data sets through a series of analysis modules, which are often
independent applications. These analyses typically need to be performed 
repeatedly over time as data are accumulated gradually.

are popular workflow management systems used to implement such pipelines for 
high-throughput analysis of genomics data. Another common approach is to use 
shell scripting to tie together different tools into an analysis pipeline. 
Whereas pipelines greatly reduce the effort required to apply different 
algorithms to large data sets, they often result in a multitude of figures, 
lists, and tables at varying levels of detail. This presents significant 
challenges for the biologists who must sift through a large amount of 
information to identify potentially interesting findings.

In the use case we describe, each run of the pipeline results in more than 11,000 figures and 
tables. In some cases, this problem can be addressed by feeding these results 
into a database with a dynamic query interface. While databases are capable of 
supporting powerful exploration tools and interactive visualizations, their 
development and maintenance require a significant investment of resources and 
their data model is less flexible than reports. This is particularly problematic
 when the tools in the pipeline are replaced as requirements change. 
Alternatively, the results can be summarized in reports.