MOTIVATION: Recent advancements in parallel sequencing methods have precipitated a surge in publicly available short-read sequence data. This has encouraged the development of novel computational tools for the de novo assembly of transcriptomes from RNA-seq data. Despite the availability of these tools, performing an end-to-end transcriptome assembly remains a programmatically involved task necessitating familiarity with best practices. Aside from quality control steps, including error correction, adapter trimming, and chimera filtration needing to be correctly used, moving data between programs often requires manual reformatting or restructuring, which can further impede throughput. Here, we introduce Semblans, a tool for streamlining the assembly process that efficiently and consistently produces high-quality transcriptome assemblies. RESULTS: Semblans abstracts the key quality control, reconstitution, and postprocessing steps of transcriptome assembly from raw short-read sequences to annotated coding sequences. Evaluating its performance against previously assembled transcriptomes on the basis of assembly quality, we find that Semblans produced higher quality assemblies for 98 of the 101 short-read runs tested. AVAILABILITY AND IMPLEMENTATION: Semblans is written in C++ and runs on Unix-compliant operating systems. Source code, documentation, and compiled binaries are hosted under the GNU General Public License at https://github.com/gladshire/Semblans.

SUMMARY: The ease with which phylogenomic data can be generated has drastically escalated the computational burden for even routine phylogenetic investigations. To address this, we present phyx : a collection of programs written in C ++ to explore, manipulate, analyze and simulate phylogenetic objects (alignments, trees and MCMC logs). Modelled after Unix/GNU/Linux command line tools, individual programs perform a single task and operate on standard I/O streams that can be piped to quickly and easily form complex analytical pipelines. Because of the stream-centric paradigm, memory requirements are minimized (often only a single tree or sequence in memory at any instance), and hence phyx is capable of efficiently processing very large datasets. AVAILABILITY AND IMPLEMENTATION: phyx runs on POSIX-compliant operating systems. Source code, installation instructions, documentation and example files are freely available under the GNU General Public License at https://github.com/FePhyFoFum/phyx. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.