A Reference Pathways Mapper for turning metagenomic functional profiles into pathway/module profiles.
java -jar omixer-rpm.jar [-a ] [-c ] [-d ] [-e ] [-h] [-i ] [--ignore-taxonomic-info] [-n] [-o ] [-s ] [-t ] [--Xdistribute]
-a,--annotation Input file annotation.
Use 1 for orthologs only files or 2 for taxonomic annotation followed by orthologs.
Defaults to 1
-c,--coverage The minimum coverage cut-off to accept a module [0.0 to 1.0].
Defaults to -1, where the coverage is learned from the coverage distribution of all modules
-d,--database The path to the modules database
-e,--export-format The output file format.
Use 1 for single tab separated files containing module id, abundance and coverage.
Use 2 for an abundance and a coverage matrices.
Defaults to 1.
-h,--help Show this help message and exit
-i,--input Path to the input matrix or input directory with one file per sample
--ignore-taxonomic-info Ignore taxonomic info from input file and infer modules for the whole metagenome instead
-n,--normalize-by-length Divide module score by its length. When combined with a median estimator, missing reactions (score = 0 )
are included when estimating the median. If the estimated score equals zero then it is replaced by
the minimum observed reaction score. If this option is specified, score calculation is based only on
the number of observed reactions
-o,--output-dir Path to the output directory
-s,--score-estimator The score estimatore.
Accepted values are [median|average|sum|min].
Defaults to median
-t,--threads Number of threads to use when mapping the modules.
Defaults to 1
--Xdistribute Experimental feature - When an ortholog is shared by N modules then its abundance is divided by N.
Input files are TAB delimited matrices of KEGG KO annotated functional profiles. An optional taxonomic annotation could also be included. For examples please refer to KO matrix and Taxon KO matrix.
The reference pathways database is a flat file where pathway/module reactions are listed following their order in the pathway. Tab-separated reactions indicate alternative reactions (OR operation), while return- and comma-separated reactions are all required for process completeness (AND operation). Below is a snippet from the human gut metabolic modules (GMMs) database, described in Vieira-Silva et al. 2016.
MF0001 arabinoxylan degradation K01209 K15921 K01181 K01198 K15531 K18205 /// MF0003 pectin degradation I K01051 K01184,K01213 K18650 /// MF0103 mucin degradation K01186 K05970 K01132 K01135 K01137 K01205 K01207 K12373 K14459 K01205 K01207 K12373 K01227 K13714 K01206 ///
You can find the complete database here. KEGG Module pathways or custom databases formatted accordingly would also work.
As defined in the database snippet above, a metabolic module is a set of alternative ortholog combinations that represent a cellular process. Given a metagenome, Omixer-RPM will select the modules that pass a user defined coverage (# observed steps / # defined steps) cutoff, then derives their abundance by selecting, for each module, the combination of orthologs that maximize its abundance.
For example, given the following module definition and profile
I: Glucose -> R1 -> R2 -> R3 -> R4 -> R5 -> O: glyceraldehyde 3-phosphate R1: K00844 K00845 R2: K01810 K06859 K13810 K15916 R3: K00850 K16370 R4: K01622 K01623 K01624 K11645 K16305 K16306 R5: K01803
K00844 10 K00845 3 K06859 7 K13810 8 K01804 12 K01622 2 K16370 5 K00703 12 K00863 15
The two possible combinations are:
A) K00844 (10) -> K13810 (8) -> K01622 (2) -> K16370 (5) -> NA B) K00845 (3) -> K06859 (7) -> K01622 (2) -> K16370 (5) -> NA
The coverage in this case is 4/5 but the average in A (25/5) is greater than in B (17/5), therefore the selected path is A and the abundance of the module is 5.
The omixer-rpmR library is available for seamless integration with R.
Omixer-RPM was developed as part of GOmixer. If you use Omixer-RPM in your work please cite:
Youssef Darzi, Gwen Falony, Sara Silva, Jeroen Raes. Towards biome-specific analysis of meta-omics data, The ISME journal, 2015
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