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LotuS: an efficient and user-friendly OTU processing pipeline.
- Source :
-
Microbiome [Microbiome] 2014 Sep 30; Vol. 2 (1), pp. 30. Date of Electronic Publication: 2014 Sep 30. - Publication Year :
- 2014
-
Abstract
- Background: 16S ribosomal DNA (rDNA) amplicon sequencing is frequently used to analyse the structure of bacterial communities from oceans to the human microbiota. However, computational power is still a major bottleneck in the analysis of continuously enlarging metagenomic data sets. Analysis is further complicated by the technical complexity of current bioinformatics tools.<br />Results: Here we present the less operational taxonomic units scripts (LotuS), a fast and user-friendly open-source tool to calculate denoised, chimera-checked, operational taxonomic units (OTUs). These are the basis to generate taxonomic abundance tables and phylogenetic trees from multiplexed, next-generation sequencing data (454, illumina MiSeq and HiSeq). LotuS is outstanding in its execution speed, as it can process 16S rDNA data up to two orders of magnitude faster than other existing pipelines. This is partly due to an included stand-alone fast simultaneous demultiplexer and quality filter C++ program, simple demultiplexer (sdm), which comes packaged with LotuS. Additionally, we sequenced two MiSeq runs with the intent to validate future pipelines by sequencing 40 technical replicates; these are made available in this work.<br />Conclusion: We show that LotuS analyses microbial 16S data with comparable or even better results than existing pipelines, requiring a fraction of the execution time and providing state-of-the-art denoising and phylogenetic reconstruction. LotuS is available through the following URL: http://psbweb05.psb.ugent.be/lotus .
- Subjects :
- Algorithms
Computational Biology instrumentation
DNA, Ribosomal
High-Throughput Nucleotide Sequencing
Microbiota genetics
RNA, Ribosomal, 16S genetics
Sequence Analysis instrumentation
Sequence Analysis, DNA
Computational Biology methods
Metagenomics methods
Sequence Analysis methods
Software
Subjects
Details
- Language :
- English
- ISSN :
- 2049-2618
- Volume :
- 2
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Microbiome
- Publication Type :
- Academic Journal
- Accession number :
- 27367037
- Full Text :
- https://doi.org/10.1186/2049-2618-2-30