This example assumes reads in FASTQ format.

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This page gives a complete pipeline to analyze 16S rRNA gene data. Of course, you should edit as needed for your reads and file locations (represented here as $PWD/).  

Create a folder containing 3  empty folders: fastq/ | fasta/ | demul |

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1- Take forward and reverse Illumina reads (R1.fastq and R2.fastq files) and join them using the method fastq-join <<<USING QIIME 1.9>>>

 

multiple_join_paired_ends.py -i raw/ -o merged/

 

2 - Quality filtering, length truncate, and convert to FASTA each joined sample <<<USING VSEARCH>>>

 

for i in $(ls fastq/); do vsearch --fastx_filter fastq/$i --fastq_maxee 1.0 --fastq_trunclen 350 --fastaout fasta/${i%.fastq}.fa; done

 

3 - Change sequence header to make file compatible with further steps <<<USING BMP PERL SCRIPT>>>. This script will generate your converted FASTA file. Sample´s name should not contain any special characters, symbols or spaces. We strongly recommend keeping samples´s name as simple as possible.

 

for i in $(ls fasta/); do bmp_demultiplexed.pl -i fasta/$i -o demul/${i%.fa}.fa -b ${i%.fa}; done

 

4 - Make a single file containing all your samples

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cat demul/*.fa > reads.fa

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5 - Dereplication <<<USING VSEARCH>>>

 

vsearch --derep_fulllength reads.fa --output derep.fa --sizeout

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6 - Abundance sort and discard singletons <<<USING VSEARCH>>>

 

vsearch --sortbysize derep.fa --output sorted.fa --minsize 2

 

7 - OTU clustering using UPARSE method <<<USING VSEARCH>>>

 

vsearch --cluster_size sorted.fa --consout otus1.fa --id 0.97

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8 - Fasta Formatter <<<FASTX TOOLKIT SCRIPT>>>

 

fasta_formatter -i otus1.fa -o formated_otus1.fa

 

9 - Renamer <<<BMP SCRIPT>>>

 

bmp-otuName.pl -i formated_otus1.fa -o otus.fa

 

10 - Map reads back to OTU database <<<VSEARCH>>>

 

vsearch --usearch_global $PWD/reads.fa --db otus.fa --strand plus --id 0.97 --uc map.txt

 

11 - Assign taxonomy to OTUS using the RDP Classifier on QIIME (use the file “otus.fa” as input file)

 

assign_taxonomy.py -i otus.fa -m rdp -o taxonomy

 

12 - Convert UC to otu-table.txt <<< BMP SCRIPT>>>

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bmp-map2qiime.py map.txt > otu_table.txt

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13 - Convert otu_table.txt to otu-table.biom <<< QIIME SCRIPT>>>

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make_otu_table.py -i otu_table.txt -t taxonomy/otus_tax_assignments.txt -o otu_table.biom

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14 - Check OTU Table  on QIIME.

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biom summarize-table -i $PWD/otu_table.biom -o results_biom_table.txt

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The generated .biom OTU table is also fully compatible with the MicrobiomeAnalyst, a user-friendly web-based platform for microbiome data analyses and visualizations, including taxonomy plots and estimates of α- and β-diversity (http://www.microbiomeanalyst.ca).