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SEPP specifications

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Unique identifier OMICS_25055
Name SEPP
Alternative name SATé-Enabled Phylogenetic Placement
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Version 1.0
Stability Stable
Maintained No

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Publication for SATé-Enabled Phylogenetic Placement

SEPP in pipeline

2018
PMCID: 5904434
PMID: 29719869
DOI: 10.1128/mSystems.00021-18

[…] fragment sequences into a large phylogeny using a divide-and-conquer approach, utilizing hmmer () to identify putative subtrees followed by pplacer for the actual fragment placement. we benchmarked sepp using 16s v4 sequence fragments and showed that it outperforms the present “state-of-the-art” approach of reconstructing de novo phylogenies and that it provides the necessary addition […]


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SEPP in publications

 (3)
PMCID: 5904434
PMID: 29719869
DOI: 10.1128/mSystems.00021-18

[…] of dealing with sotus (building a de novo tree from the short sequences) can provide incorrect results in human gut metagenomic studies and show that phylogenetic placement of the new sequences with sepp resolves this problem while also yielding other benefits over existing methods., recent algorithmic advances in amplicon-based microbiome studies enable the inference of exact amplicon sequence […]

PMCID: 5034103
PMID: 27530749
DOI: 10.1038/emi.2016.90

[…] near full-length sequences. next, hmmsearch was used to find all orfs from the fragmentary contigs that had a hit to the profile hmm (93 total orfs hit). we inserted the orfs into the ml tree using sepp (saté-enabled phylogenetic placement) (v2), a phylogenetic placement method that can accurately place evolutionarily divergent sequences., validation of contigs was carried out using two […]

PMCID: 3516148
PMID: 23023983
DOI: 10.1093/bioinformatics/bts578

[…] see supplementary material for the details., the –addfragments option performed well in comparison with existing methods that were specially designed for aligning short sequences. for the sepp dataset, as shown in , it generally outperformed papara and pagan, but in the easiest case (1000m4), the difference was minor. for the pagan dataset (see supplementary table s1), the difference […]


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SEPP institution(s)
Department of Computer Science, University of Texas at Austin, Austin, TX, USA

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