Example Pipeline Qiime

Typical QIIME Pipeline

• The following pipeline is generated from the Config file: chinaQiimeClosedPaired.properties.
• Only 6 BioModules are listed in the Config file
• The pipeline executes 15 BioModules at runtime after 6 implicit and 3 dependent modules are added by the system.

1. ImportMetadata is a prerequisite implicit module that is always run as the 1st module.
2. RegisterNumReads counts the number of reads per sample and stores the total in the metadata file in a field named Num_Reads.
3. PearMergeReads is a prerequisite module added when input.dirs contains paired sequence files since QIIME only accepts forward reads.
4. AwkFastaConverter is a prerequisite module added when input.dirs contains fastq sequence files since QIIME only accepts fasta format.
5. BuildQiimeMapping is an implicit module added to all QIIME pipelines to convert the metadata file into a QIIME mapping file.
6. Select 1 OTU picking module [ QiimeClosedRefClassifier / QiimeDeNovoClassifier / QiimeOpenRefClassifier ]
   • Each runs add_qiime_labels.py to create the required multiplexed input file before calling the OTU picking script.
   • Each outputs 1+ otu_table.biom files.
7. MergeQiimeOtuTables is a post-requisite module after QiimeClosedRefClassifier (if selected) used to combine batched output into a single otu_table.biom file.
   • Cannot be run after other OTU picking modules.
   • Only necessary if #samples > script.batchSize.
8. QiimeClassifier is an implicit post-requisite module that runs after the OTU-picking module to produce taxonomy-level OTU reports.
9. QiimeParser is a post-requisite module that runs after the classifier to create OTU abundance tables from the taxonomy-level reports.
10. Normalizer log-normalizes the OTU abundance tables.
11. AddMetadataToOtuTables is a pre-requisite module that runs before the 1st R module.
12. CalculateStats is a pre-requisite module that runs before any other R module.
13. BuildMdsPlots generates PCOA analysis and plots the top MDS axis.
14. BuildPvalHistograms plots p-value histograms to identify significant metadata fields.
15. BuildOtuPlots generates box plots and scatterplots to identify significant OTU-metadata correlations.