Search for: All records

Graphs are powerful tools for modeling and analyzing molecular interaction networks. Graphs typically represent either undirected physical interactions or directed regulatory relationships, which can obscure a particular protein’s functional context. Graphlets can describe local topologies and patterns within graphs, and combining physical and regulatory interactions offer new graphlet configurations that can provide biological insights. We present GRPhIN, a tool for characterizing graphlets and protein roles within graphlets in mixed physical and regulatory interaction networks. We describe the graphlets of mixed networks in B. subtilis, C. elegans, D. melanogaster, D. rerio, and S. cerevisiae and examine local topologies of proteins and subnetworks related to the oxidative stress response pathway. We found a number of graphlets that were abundant in all species, specific node positions (orbits) within graphlets that were over-represented in stress-associated proteins, and rarely-occurring graphlets that were over-represented in oxidative stress subnetworks. These results showcase the potential for using graphlets in mixed physical and regulatory interaction networks to identify new patterns beyond a single interaction type. 

Third-generation sequencing technologies can generate very long reads with relatively high error rates. The lengths of the reads, which sometimes exceed one million bases, make them invaluable for resolving complex repeats that cannot be assembled using shorter reads. Many high-quality genome assemblies have already been produced, curated, and annotated using the previous generation of sequencing data, and full re-assembly of these genomes with long reads is not always practical or cost-effective. One strategy to upgrade existing assemblies is to generate additional coverage using long-read data, and add that to the previously assembled contigs. SAMBA is a tool that is designed to scaffold and gap-fill existing genome assemblies with additional long-read data, resulting in substantially greater contiguity. SAMBA is the only tool of its kind that also computes and fills in the sequence for all spanned gaps in the scaffolds, yielding much longer contigs. Here we compare SAMBA to several similar tools capable of re-scaffolding assemblies using long-read data, and we show that SAMBA yields better contiguity and introduces fewer errors than competing methods. SAMBA is open-source software that is distributed at https://github.com/alekseyzimin/masurca .