Phylometabolomic Trees
Summary
Generating matrices for phylometabolomic analysis is a two-step process. In the first step, sets of metadata triplets are created. In the second step, those sets are used as input to the actual calculator.
Step 1 - Triplets
Making a post request to
``` http://bindiscover.metabolomics.us:4999/treemetadataresource/ ```With the format
{
"species":"10114", #any NCBI species or parent ID
"organ":"A03.620", #any MeSH organ ID
"disease":"No Disease", #any MeSH disease ID
"species_organ_disease":["arabidopsis thaliana - Plant Roots - No Disease"] #any triplet from our data
}
Where values in this dictionary are nodes from the NCBI taxonomy and MeSH Hierarchies AND/OR individual triplets will yield a record-oriented metadata table, e.g.
"[
{\"triplet_id\":\"rattus rattus - Liver - No Disease\",\"sample_count\":221},
{\"triplet_id\":\"arabidopsis thaliana - Plant Roots - No Disease\",\"sample_count\":408}
]"
Step 2 - Phylometabolomic Matrices
Making a post request to
http://bindiscover.metabolomics.us:4999/treeresource/
with the format
{
"metadata_triplets":["salmonella enterica - Cells - No Disease", "faecalibacterium prausnitzii - Cells - No Disease", "mycoplasma - Cells - No Disease"],
"data_type":"percent_present", #
"bin_type":"knowns" #options are "knowns" (known compounds) or "all" (all compounds)
}
will yield the core information for the phylometabolomic trees, eg
"[
{\"2\":0.9848484848,\"3\":0.8484848485,\"4\":0.8787878788,\"5\":0.9848484848,\"6\":0.9090909091,\"8\":0.6363636364,\"9\":0.2272727273,\"10\":0.9242424242,...
]"