mothur tutorial STAMPS, 2013 Kevin R. Theis Department of Zoology BEACON Center for the Study of Evolution in Action Michigan State University
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1 mothur tutorial STAMPS, 2013 Kevin R. Theis Department of Zoology BEACON Center for the Study of Evolution in Action Michigan State University
2 mothur Mission to develop a single piece of open-source, expandable software to fill the bioinformatics needs of the microbial ecology community Primary use screening, processing, aligning & clustering of Sanger, 454 or Illumina (16S rrna) amplicons generating a high-quality, effectively normalized shared file (i.e. counts of OTUs per sample) gaining general taxonomic information about the OTUs in your study system (RDP Taxonomic Classifier) Tutorial objective to develop proficiency in mothur and learn where to find help outside the context of this course theiskev@msu.edu
3 mothur Pat Schloss Microbiology & Immunology, University of Michigan Mothur manual Schloss Lab SOPs Intensive, 3d workshops in Detroit
4 mothur references s-libshuff, dotur, sons Schloss, P., Larget, B. & Handelsman, J. Integration of microbial ecology and statistics: a test to compare gene libraries. Applied and Environmental Microbiology 70, (2004). Schloss, P. D. & Handelsman, J. Introducing DOTUR, a computer program for defining operational taxonomic units and estimating species richness. Applied and Environmental Microbiology 71, (2005). Schloss, P. D. & Handelsman, J. Introducing SONS, a tool for operational unit-based comparisons of microbial community memberships and structures. Applied and Environmental Microbiology 72, (2006). mothur Schloss, P. D. et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology 75, (2009). Schloss, P. D. A high-throughput DNA sequence aligner for microbial ecology studies. PLoS One 4 (2009). Schloss, P. D. The effects of alignment quality, distance calculation method, sequence filtering, and region on the analysis of 16S rrna gene-based studies. PLoS Comput. Biol. 6 (2010). Schloss, P. D., Gevers, D. & Westcott, S. L. Reducing the effects of PCR amplification and sequencing artifacts on 16S rrna-based studies. PLoS One 6, e27310 (2011). Schloss, P. D. & Westcott, S. L. Assessing and improving methods used in operational taxonomic unit-based approaches for 16S rrna gene sequence analysis. Applied and Environmental Microbiology 77, (2011). Schloss, P. D. Secondary structure improves OTU assignments of 16S rrna gene sequences. ISME J 7, (2013). Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K. & Schloss, P. D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Applied and Environmental Microbiology, doi: /aem (2013).
5 mothur Updated versions are released every few months First release, v1.1.0, March 2009 Last release, v1.31.2, June 2013 Approaches Taxonomy OTUs Phylogeny Sequencing systems Sanger 454 Illumina Tutorials for OTU-based approach Illumina
6 mothur workflow 454 sff.info trim.flows shhh.flows trim.seqs unique.seqs align.seqs screen.seqs filter.seqs unique.seqs pre.cluster chimera.uchime remove.seqs classify.seqs remove.lineage [assess error rate] dist.seqs cluster make.shared count.groups sub.sample classify.otu Illumina make.contigs screen.seqs uniques.seqs count.seqs pcr.seqs Data for hypothesis testing
7 Reducing sequencing errors 454 PyroNoise more & longer reads Sliding window (50 nt, Q35) Hard trim (250 nt) Illumina Algorithms detailed in Kozich et al Briefly summarized in MiSeq SOP (Schloss et al. 2011; Kozich et al. 2013; Quince et al. 2011, doi: / )
8 Sequence alignment You supply a fastaformatted reference alignment Links to Greengenes SILVA kmer & Needleman- Wunsch approach (Schloss 2009; Schloss 2010; Schloss 2013; Pruesse et al. 2007, doi: /nar/gkm864; Pruesse et al. 2012, doi: /bioinformatics/bts252 )
9 Pre-clustering sequences Further reduce sequence noise Aims to integrate rare, erroneous sequences into prominent ones Generally, combine sequences with 1 nt difference per 100 nt (based on single-linkage preclustering; Huse et al. 2010, doi: /j x)
10 Removing chimeric sequences UPARSE? Identify & remove chimeras Several options Bellerophon Pintail ChimeraCheck Ccode ChimeraSlayer UCHIME de novo (Edgar et al. 2011, doi: /bioinformatics/btr38)
11 Removing contaminants Remove sequences from: mitochondria chloroplasts archaea eukaryotes unknown
12 Clustering sequences Algorithms nearest neighbor average neighbor furthest neighbor (*) Distances e.g. 0.03, 0.10, 0.20 (Schloss & Handelsman 2005; Schloss & Westcott 2011; Schloss 2013)
13 Finalizing shared files Normalization / Subsampling sequence depth, or sample coverage Remove singletons
14 Specific file types worth noting 454.oligos.names.groups.accnos Illumina.files.count_table
15 Options for running mothur Windows, Mac, Linux Interactive Batch GUI In my test runs, I used 2 processors Both 454 & Illumina tutorials took ~ hrs 454, start with trim.seqs (the output files have been provided) You will not do the using quality scores approach You can copy & paste all commands but, as Sue correctly noted with R, you won t learn it this way
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