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predictTrophicMode: Trophic Mode Prediction Tool, (c) John A. Burns, 2017

This tool runs in R, using the rscript command line tool, which should be platform independent.


Dependencies:

To run this tool in default mode, matching the analysis done in the corresponding manuscript, you must install the following packages in your R distribution:

gplots, ggplot2, ggrepel, matrixStats, RColorBrewer, randomForest, rlist, optparse, pnn, basicPlotteR, pavo, concaveman, mapproj, purrr

To run this tool in advanced mode, with additional functionality for comparing between any two groups and limiting the analysis to the proteins in your favorite genome/s, you must install the following additional packages in your R distribution:

topGO, plyr, Boruta


Usage:

For either mode, the first step is to search the ~14k HMMs against the proteins from your genome or transcriptome. The 14k+ HMMs defining the proteins in the moodel can be downloaded here: "https://figshare.com/articles/DiverseGenome-AllvAll-cluster_HMMs/5285818". Unzip the file "phag_nonphag-allVall-any3diverse.hmmCAT.hmm.gz" and run hmmsearch as follows. Will only work with proteins. The script expects a list of models that have a significant hit (evalue<=1e-5) to some protein in your genome/transcriptomes of interest. To get such a list, run the following commands on a computer/server with HMMER3 installed.

define files, names

species=[your species here]
filename=[name of your protein file here]
HMMs=[path to]/phag_nonphag-allVall-any3diverse.hmmCAT.hmm

run hmmsearch

hmmsearch --tblout $species.x.phag_nonphag-allVall-any3diverse.hmmsearchOUT-tbl.txt --cpu 8 $HMMs $filename

filter for significant hits (full sequence evalue <= 1e-5, any domain evalue <=1e-4) *evalue threshold used to generate the model: full sequence evalue <= 1e-5, any domain evalue <=1e-4. For predictions to be accurate, must use same threshold here. If you would like to experiment with changing that threshold, you must rebuild the presense absence matrix by re-thresholding all of the default organisms. To do so, run hmmsearch against all of those genomes, or contact the author for the raw hmmsearch output files.

the following commands can be used to get the list of signifcant hits in the correct format for the prediction tool (in BASH). The output files with the format "species_sigModels.txt" should contain a list of HMM names that are significant hits to at least 1 protein in your target genome:

sigfile=${species}_sigHits.txt
sigModel=${sigfile//_sigHits.txt/_sigModels.txt}
echo $sigfile
echo $sigModel
grep -v "^#" $species.x.phag_nonphag-allVall-any3diverse.hmmsearchOUT-tbl.txt | awk '$5<=1e-5 && $8<=1e-4' > $sigfile
awk '{print $3}' $sigfile | sort -u > $sigModel

Place the file/s containing the list of significant HMMs into the directory "TrophicModePredictionTool/TestGenomes"

In Windows (tested in Windows PowerShell) or Linux, cd to the directory "TrophicModePredictionTool"

Default mode, testing against the models outlined in the corresponding manuscript:

run the script: runModel.r

  • In Windows PowerShell it might be run like so (from within TrophicModePredictionTool):

    'C:\Program Files\R\R-3.3.1\bin\Rscript.exe' .\runModel.r

  • In Linux, it is much the same: [path to]Rscript runModel.r

If the model is run exactly as above, it will finish in about 30 seconds and will output a series of plots and predictions into the directory "TrophicModePredictionTool/modelOUTPUT/defaultModelOUTPUT" and its subdirectories. The outputs are organized by type of analysis.

NOTE on Mollweide projection: Legend is in the file: "modelOUTPUT/defaultModelOUTPUT/Legend_MollweideProj.pdf" Shaded region legend is in the file: "modelOUTPUT/defaultModelOUTPUT/MollweideShading.pdf" To make a publication-ready figure, combine the Mollweide projection plot with the information from the two legend files.


Advanced mode:

Advanced mode allows the user control over the groupings, and the ability to limit the model to proteins present in a single or set of genomes.

To change the groupings, edit the files: "AdvancedMode/orgGroups/Group1.txt" and/or "Group2.txt" ***Note: The species names in the files Group1.txt and Group2.txt must exactly match (case sensitive) the species names given to the model.

The advanced model will look for proteins and GO categories relatively enriched in Group1 and depleted in Group2.

The model comes with a presence/absence matrix containing set of default genomes, to remove any of them from the analysis entirely, include them in the file: AdvancedMode/orgGroups/removeOrgs.txt

Note, if they are removed from the analysis, they also need to be removed from the training set files.

Note2: must have exact matches here as well.

To limit the model to proteins present in a single genome or set of genomes (For example if it is a small genome, but you are certain it has the character you are interested in), include those species names in the file: "AdvancedMode/orgGroups/limitOrgs.txt". Those species will automatically be removed from the training sets.


Options

To see a list of options, use:

Rscript runModel.r --help

That will print the following: Options: -m MODE, --mode=MODE use in "manuscript" (fast) or "advanced" (slower) mode? Manuscript mode runs the model as outlined in the paper. Advanced mode allows comparisons using the 14k HMMs discussed in the paper on any two groups of organisms. [default= manuscript]

    -l LIMIT, --limit=LIMIT
            limit to specific genome/set of genomes Y or N? [default= N]

    -p PHAGOSOME, --phagosome=PHAGOSOME
            include proteins from phagosome Y or N? [default= N]

    -b BORUTA, --boruta=BORUTA
            how many times to iterate Boruta algorithm? For testing, 100 is a good number [default= 10000]

    -r REMOVE_ORGANISMS, --remove_organisms=REMOVE_ORGANISMS
            remove some or all default organisms? Y or N ***Note: cannot remove default organisms if they are used in the training set!!! default= N]

    --gene_pval=GENE_PVAL
            pvalue threshold for difference between group1 and group2 for each gene [default= 0.05]

    --GO_pval=GO_PVAL
            pvalue for GO term enrichment [default= 0.2]

    -h, --help
            Show this help message and exit

Running advanced mode

use the flags listed above to change the different options. None are required. If the default files are unaltered and no flags are given other than "-m advanced", the script will regenerate the model from the manuscript. If the files are altered, or any flags are used, the model will change. The "-p" flag will force the model to include proteins identified as part of the physical phagosome, regardless of whether or not they are differentially found between group 1 and group 2. Advanced mode takes between 3-10 minutes to run.

Note, in Windows PowerShell, I've noticed that the script sometimes gets paused somehow and it helps to occasionally hit enter if it looks like it is stuck.

As in "manuscript" (default) mode, the output for advanced mode is organized by type of analysis and appears in the directory "TrophicModePredictionTool/modelOUTPUT/advancedModeOUTPUT" and its subdirectories.

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