MLgsc: A Maximum-Likelihood General Sequence Classifier

被引:3
|
作者
Junier, Thomas [1 ,2 ]
Herve, Vincent [1 ,3 ]
Wunderlin, Tina [1 ]
Junier, Pilar [1 ]
机构
[1] Univ Neuchatel, Microbiol Lab, CH-2000 Neuchatel, Switzerland
[2] Swiss Inst Bioinformat, Vital IT Grp, Lausanne, Vaud, Switzerland
[3] Univ Lausanne, Inst Earth Sci, Lab Biogeosci, Lausanne, Vaud, Switzerland
来源
PLOS ONE | 2015年 / 10卷 / 07期
基金
瑞士国家科学基金会;
关键词
TAXONOMIC CLASSIFICATION; SPORULATION; ALIGNMENT; SEARCH; PERFORMANCE; PLACEMENT; ACCURACY;
D O I
10.1371/journal.pone.0129384
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
We present software package for classifying protein or nucleotide sequences to user-specified sets of reference sequences. The software trains a model using a multiple sequence alignment and a phylogenetic tree, both supplied by the user. The latter is used to guide model construction and as a decision tree to speed up the classification process. The software was evaluated on all the 16S rRNA gene sequences of the reference dataset found in the GreenGenes database. On this dataset, the software was shown to achieve an error rate of around 1% at genus level. Examples of applications based on the nitrogenase subunit NifH gene and a protein-coding gene found in endospore-forming Firmicutes is also presented. The programs in the package have a simple, straightforward command-line interface for the Unix shell, and are free and open-source. The package has minimal dependencies and thus can be easily integrated in command-line based classification pipelines.
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页数:12
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