Background: The scales of bioinformatic projects are constantly growing, and in tandem, the amount of available sequence data continuously increases. Consequently, efficient and human-friendly visualisation of the data becomes increasingly challenging, but is still essential for making interpretations and discovering unexpected properties of the data. Multiple sequence alignments can provide valuable insight into the properties of protein families, and are an integral part of many bioinformatic methods. Ideally, visualisation should simultaneously be comprehensive and detailed, and never distract with irrelevant information. It also needs to oer natural and responsive ways of exploring the data, as well as provide consistent views in order to facilitate comparisons between datasets.
Results: MSAView is a modular, congurable and extensible package for analysing and visualising multiple sequence alignments and sequence features. It has a fast graphical user interface that remains responsive even for large datasets, as well as a powerful command line client which allows for exible batch work. It is highly congurable and has a user extendable p reset library, as well as a plugin architecture which allows for straightforward extension of the program's capabilities. Internally, MSAView uses self-assembling functional components to construct the data ows, which both helps reduce unnecessary computation and facilitates adding new features to the program.
MSAView is written in python, and all the program's functionality is directly accessible via the python API for more advanced operations.
We also present two conservation measures which the program can visualise as a means to quickly find abnormalities in the alignment; alignment divergences which highlight unusual residues or deletions, and sequence conformances which can help expose sequences that dier from their siblings at crucial positions.
Conclusions: MSAView is a multiple sequence alignment visualiser that has been used in several projects, both for interactive inspection of unknown protein families and to generate consistent views for hundreds of protein families at a time. It can integrate and display data from online sources, and it can launch external viewers for additional details, such as structures and database pages. The graphical user interface remains responsive on modern workstations, even for large datasets.