PyNAST: A flexible tool for aligning sequences to a template alignment

Department of Chemistry and Biochemistry, University of Colorado at Boulder, Boulder, CO, USA.
Bioinformatics (Impact Factor: 4.98). 11/2009; 26(2):266-7. DOI: 10.1093/bioinformatics/btp636
Source: PubMed

ABSTRACT The Nearest Alignment Space Termination (NAST) tool is commonly used in sequence-based microbial ecology community analysis, but due to the limited portability of the original implementation, it has not been as widely adopted as possible. Python Nearest Alignment Space Termination (PyNAST) is a complete reimplementation of NAST, which includes three convenient interfaces: a Mac OS X GUI, a command-line interface and a simple application programming interface (API).
The availability of PyNAST will make the popular NAST algorithm more portable and thereby applicable to datasets orders of magnitude larger by allowing users to install PyNAST on their own hardware. Additionally because users can align to arbitrary template alignments, a feature not available via the original NAST web interface, the NAST algorithm will be readily applicable to novel tasks outside of microbial community analysis.
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Available from: Todd Z DeSantis, Sep 26, 2015
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    • "( The analysis process was as follows: (1) removal of low-quality or ambiguous sequencing reads (reads with lengths <150 bp, >0 ambiguous bases, >6 homopolymers, primer mismatches, or average quality scores <25); (2) assignment of the multiplexed reads to samples through examination of the 12-bp barcode; (3) removal of all putative chimeras, which can be detected by the Usearch tool using a chimera-free reference database according to the Uchime algorithm [28]; (4) assignment of similar sequences to operational taxonomic units (OTUs) via the clustering method at a 97% sequence similarity level [29]; (5) alignment of a representative sequence from each OTU with Python Nearest Alignment Space Termination (PyNAST) [30] "
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    • "Operational Taxonomic Units (OTUs) were picked with 97% sequence similarity using uclust (Edgar, 2010). Most abundant sequences found in each OTU were picked as representative sequences and aligned against Greengenes core set (DeSantis et al., 2006) using PyNAST (Caporaso, Bittinger et al., 2010) with a minimum sequence identity of 75% and a minimum sequence length of 300 nt. Taxonomy was assigned to the representative sequences using Ribosomal Database Project (RDP) Classifier with minimum confidence score of 0.8 (Cole et al., 2007). "
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    • "Filtered alignments were used to generate an uncorrected pairwise distance matrix, followed by binning the sequences into operational taxonomic units (OTUs) at 3, 6, 8, 10, and 15% cutoffs. For phylogenetic placement, representative OTUs defined at the 3% cutoff (OTU 0.03 ) were classified with Greengenes taxonomy scheme using the PyNAST pipeline (Caporaso et al., 2010). Phylum level affiliation of sequences were determined according to the classifier output, and sequences with less than 85% similarity to their closest relative in Greengenes database were considered unclassified. "
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