MOTIVATION: Sequence analyses oriented to investigate specific features, patterns and functions of protein and DNA/RNA sequences usually require tools based on graphic interfaces whose main characteristic is their intuitiveness and interactivity with the user's expertise, especially when curation or primer design tasks are required. However, interface-based tools usually pose certain computational limitations when managing large sequences or complex datasets, such as genome and transcriptome assemblies. Having these requirments in mind we have developed SeqEditor an interactive software tool for nucleotide and protein sequences' analysis. RESULT: SeqEditor is a cross-platform desktop application for the analysis of nucleotide and protein sequences. It is managed through a Graphical User Interface and can work either as a graphical sequence browser or as a fasta task manager for multi-fasta files. SeqEditor has been optimized for the management of large sequences, such as contigs, scaffolds or even chromosomes, and includes a GTF/GFF viewer to visualize and manage annotation files. In turn, this allows for content mining from reference genomes and transcriptomes with similar efficiency to that of command line tools. SeqEditor also incorporates a set of tools for singleplex and multiplex PCR primer design and pooling that uses a newly optimized and validated search strategy for target and species-specific primers. All these features make SeqEditor a flexible application that can be used to analyses complex sequences, design primers in PCR assays oriented for diagnosis, and/or manage, edit and personalize reference sequence datasets. AVAILABILITYAND IMPLEMENTATION: SeqEditor was developed in Java using Eclipse Rich Client Platform and is publicly available at https://gpro.biotechvana.com/download/SeqEditor as binaries for Windows, Linux and Mac OS. The user manual and tutorials are available online at https://gpro.biotechvana.com/tool/seqeditor/manual. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Jansson and Sung showed that, given a dense set of input triplets T (representing hypotheses about the local evolutionary relationships of triplets of taxa), it is possible to determine in polynomial time whether there exists a level-1 network consistent with T, and if so, to construct such a network [24]. Here, we extend this work by showing that this problem is even polynomial time solvable for the construction of level-2 networks. This shows that, assuming density, it is tractable to construct plausible evolutionary histories from input triplets even when such histories are heavily nontree-like. This further strengthens the case for the use of triplet-based methods in the construction of phylogenetic networks. We also implemented the algorithm and applied it to yeast data.