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Motivation: One basic step in many bioinformatics analyses is the multiple sequence alignment. One of the state-of-the-art tools to perform multiple sequence alignment is PASTA (Practical Alignments using SATe' and TrAnsitivity). PASTA supports multithreading but it is limited to process datasets on shared memory systems. In this work we introduce PASTASpark, a tool that uses the Big Data engine Apache Spark to boost the performance of the alignment phase of PASTA, which is the most expensive task in terms of time consumption. Results: Speedups up to 10° with respect to single-threaded PASTA were observed, which allows to process an ultra-large dataset of 200 000 sequences within the 24-h limit. [ABSTRACT FROM AUTHOR]

Motivation FastTree-2 is one of the most successful tools for inferring large phylogenies. With speed at the core of its design, there are still important issues in the FastTree-2 implementation that harm its performance and scalability. To deal with these limitations, we introduce VeryFastTree, a highly tuned implementation of the FastTree-2 tool that takes advantage of parallelization and vectorization strategies to boost performance. Results VeryFastTree is able to construct a tree on a standard server using double-precision arithmetic from an ultra-large 330k alignment in only 4.5 h, which is 7.8× and 3.5× faster than the sequential and best parallel FastTree-2 times, respectively. Availability and implementation VeryFastTree is available at the GitHub repository: https://github.com/citiususc/veryfasttree. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]