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SINA aligns nucleotide sequences to match a pre-existing MSA using a graph based alignment algorithm similar to PoA. The graph approach allows SINA to incorporate information from many reference sequences building without blurring highly variable regions. While pure NAST implementations depend highly on finding a good match in the reference database, SINA is able to align sequences relatively distant to references with good quality and will yield a robust result for query sequences with many close reference.
.. _SILVA: https://www.arb-silva.de .. _ARB: https://www.arb-home.de
An online version for submitting small batches of sequences is made
available by the SILVA project as part of their
ACT: Alignment, Classification and Tree Service <https://www.arb-silva.de/aligner>
.
In addition to SINA's alignment and classification stages, ACT allows directly building
phylogenetic trees with RAxML or FastTree from your sequences and (optionally)
additional sequences chosen using SINA's add-neighbors feature.
The preferred way to install SINA locally is via Bioconda <https://bioconda.github.io>
_.
If you have a working Bioconda installation, just run::
conda create -n sina sina
conda activate sina
Alternatively, self-contained images are available at
https://github.com/epruesse/SINA/releases. Choose the most recent tar.gz
appropriate for your operating system and unpack::
tar xf sina-1.7.3-dev-dev-linux.tar.gz cd sina-1.7.3-dev-dev ./sina
The full documentation is available at https://sina.readthedocs.io.
The algorithm is explained in the paper:
Elmar Pruesse, Jörg Peplies, Frank Oliver Glöckner; SINA: Accurate
high-throughput multiple sequence alignment of ribosomal RNA
genes. Bioinformatics 2012; 28 (14): 1823-1829.
doi:10.1093/bioinformatics/bts252 <https://doi.org/10.1093/bioinformatics/bts252>
_