NanoStriDE: normalization and differential expression analysis of NanoString nCounter data.

BACKGROUND: The nCounter analysis system (NanoString Technologies, Seattle, WA) is a technology that enables the digital quantification of multiplexed target RNA molecules using color-coded molecular barcodes and single-molecule imaging. This system gives discrete counts of RNA transcripts and is capable of providing a high level of precision and sensitivity at less than one transcript copy per cell. RESULTS: We have designed a web application compatible with any modern web browser that accepts the raw count data produced by the NanoString nCounter analysis system, normalizes it according to guidelines provided by NanoString Technologies, performs differential expression analysis on the normalized data, and provides a heatmap of the results from the differential expression analysis. CONCLUSION: NanoStriDE allows biologists to take raw data produced by a NanoString nCounter analysis system and easily interpret differential expression analysis of this data represented through a heatmap. NanoStriDE is freely accessible to use on the NanoStriDE website and is available to use under the GPL v2 license.

Experiences with workflows for automating data-intensive bioinformatics.

High-throughput technologies, such as next-generation sequencing, have turned molecular biology into a data-intensive discipline, requiring bioinformaticians to use high-performance computing resources and carry out data management and analysis tasks on large scale. Workflow systems can be useful to simplify construction of analysis pipelines that automate tasks, support reproducibility and provide measures for fault-tolerance. However, workflow systems can incur significant development and administration overhead so bioinformatics pipelines are often still built without them. We present the experiences with workflows and workflow systems within the bioinformatics community participating in a series of hackathons and workshops of the EU COST action SeqAhead. The organizations are working on similar problems, but we have addressed them with different strategies and solutions. This fragmentation of efforts is inefficient and leads to redundant and incompatible solutions. Based on our experiences we define a set of recommendations for future systems to enable efficient yet simple bioinformatics workflow construction and execution.