SUMMARY: The graphical fragment assembly (GFA) formats are emerging standard formats for the representation of sequence graphs. Although GFA 1 was primarily targeting assembly graphs, the newer GFA 2 format introduces several features, which makes it suitable for representing other kinds of information, such as scaffolding graphs, variation graphs, alignment graphs and colored metagenomic graphs. Here, we present GfaViz, an interactive graphical tool for the visualization of sequence graphs in GFA format. The software supports all new features of GFA 2 and introduces conventions for their visualization. The user can choose between two different layouts and multiple styles for representing single elements or groups. All customizations can be stored in custom tags of the GFA format itself, without requiring external configuration files. Stylesheets are supported for storing standard configuration options for groups of files. The visualizations can be exported to raster and vector graphics formats. A command line interface allows for batch generation of images. AVAILABILITY AND IMPLEMENTATION: GfaViz is available at https://github.com/ggonnella/gfaviz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: GFA 1 and GFA 2 are recently defined formats for representing sequence graphs, such as assembly, variation or splicing graphs. The formats are adopted by several software tools. Here, we present GfaPy, a software package for creating, parsing and editing GFA graphs using the programming language Python. GfaPy supports GFA 1 and GFA 2, using the same interface and allows for interconversion between both formats. The software package provides a simple interface for custom record types, which is an important new feature of GFA 2 (compared to GFA 1). This enables new applications of the format. AVAILABILITY AND IMPLEMENTATION: GfaPy is available open source at https://github.com/ggonnella/gfapy and installable via pip. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: Ongoing improvements in throughput of the next-generation sequencing technologies challenge the current generation of de novo sequence assemblers. Most recent sequence assemblers are based on the construction of a de Bruijn graph. An alternative framework of growing interest is the assembly string graph, not necessitating a division of the reads into k-mers, but requiring fast algorithms for the computation of suffix-prefix matches among all pairs of reads. RESULTS: Here we present efficient methods for the construction of a string graph from a set of sequencing reads. Our approach employs suffix sorting and scanning methods to compute suffix-prefix matches. Transitive edges are recognized and eliminated early in the process and the graph is efficiently constructed including irreducible edges only. CONCLUSIONS: Our suffix-prefix match determination and string graph construction algorithms have been implemented in the software package Readjoiner. Comparison with existing string graph-based assemblers shows that Readjoiner is faster and more space efficient. Readjoiner is available at http://www.zbh.uni-hamburg.de/readjoiner.