mOTUs Parameters

Output Parameters

There are number of optional parameters that can be provided to profile to modify the output format, but not the actual mOTUs algorithm.

-I FILE         save the result of bwa in bam format (intermediate step) [None]
-M FILE         save the mgc reads count (intermediate step) [None]
-e              profile only reference species (ref_mOTUs)
-c              print result as counts instead of relative abundances
-p              print NCBI id
-u              print the full name of the species
-q              print the full rank taxonomy
-B              print result in BIOM format
-C STR          print result in CAMI format (BioBoxes format 0.9.1)
                Values: [precision, recall, parenthesis]
-k STR          taxonomic level [mOTU]
                Values: [kingdom, phylum, class, order, family, genus, mOTU]

We can for instance modify our output to see counts, rather than relative abundances, and move our analysis to the family level, only allowing reference species:

motus profile -f <forward reads> -r <reverse reads> -o <output file> -t 12 -e -c -k family

The output looks something like this:

#consensus_taxonomy     M01.1-V1-stool-metaG
Nitrososphaeraceae      0
Oscillochloridaceae     0
...
Micrococcaceae  0
Erysipelotrichaceae     38
Streptococcaceae        13
candidatus Midichloriaceae      0
...
candidatus Poribacteria fam. incertae sedis     0
candidatus Saccharibacteria fam. incertae sedis 0
-1      11415

Algorithm Parameters

There are also a number of parameters that modify the operation of the mOTUs algorithm.

-g INT          number of marker genes cutoff: 1=higher recall, 10=higher precision [3]
-l INT          min. length of alignment for the reads (number of nucleotides) [75]
-t INT          number of threads [1]
-v INT          verbose level: 1=error, 2=warning, 3=message, 4+=debugging [3]
-y STR          type of read counts [insert.scaled_counts]
                Values: [base.coverage, insert.raw_counts, insert.scaled_counts]

The result with highest sensitivity is obtained with -g 1 -l 30 -y base.coverage, allowing to detect low abundance bugs (at the cost of having more false positives).

The result with highest precision is obtained with -g 6 -l 75 -y insert.scaled_counts, reducing the false positives to the minimum.

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We will now produce two additional outputs for later comparison with the default output of profile. Run the same set of data as you chose initially, but with highest sensitivity, then highest precision parameters. Then merge these two with the default set of data to make one .motu file.