Simple food over representation analysis (ORA)

Compiled date: 2026-07-25

Last edited: 2022-01-12

License: GPL-3

Installation

Run the following code to install the Bioconductor version of the package.

# install.packages("BiocManager")
BiocManager::install("fobitools")

Load fobitools

library(fobitools)

You can also load some additional packages that will be very useful in this vignette.

library(dplyr)
library(kableExtra)

metaboliteUniverse and metaboliteList

In microarrays, for example, we can study almost all the genes of an organism in our sample, so it makes sense to perform an over representation analysis (ORA) considering all the genes present in Gene Ontology (GO). Since most of the GO pathways would be represented by some gene in the microarray.

This is different in nutrimetabolomics. Targeted nutrimetabolomics studies sets of about 200-500 diet-related metabolites, so it would not make sense to use all known metabolites (for example in HMDB or CHEBI) in an ORA, as most of them would not have been quantified in the study.

In nutrimetabolomic studies it may be interesting to study enriched or over represented foods/food groups by the metabolites resulting from the study statistical analysis, rather than the enriched metabolic pathways, as would make more sense in genomics or other metabolomics studies.

The Food-Biomarker Ontology (FOBI) provides a biological knowledge for conducting these enrichment analyses in nutrimetabolomic studies, as FOBI provides the relationships between several foods and their associated dietary metabolites (Castellano-Escuder et al. 2020).

Accordingly, to perform an ORA with the fobitools package, it is necessary to provide a metabolite universe (all metabolites included in the statistical analysis) and a list of selected metabolites (selected metabolites according to a statistical criterion).

Here is an example:

# select 300 random metabolites from FOBI
idx_universe <- sample(nrow(fobitools::idmap), 300, replace = FALSE)
metaboliteUniverse <- fobitools::idmap %>%
  dplyr::slice(idx_universe) %>%
  pull(FOBI)

# select 10 random metabolites from metaboliteUniverse that are associated with 'Red meat' (FOBI:0193), 
# 'Lean meat' (FOBI:0185) , 'egg food product' (FOODON:00001274), 
# or 'grape (whole, raw)' (FOODON:03301702)
fobi_subset <- fobitools::fobi %>% # equivalent to `parse_fobi()`
  filter(FOBI %in% metaboliteUniverse) %>%
  filter(id_BiomarkerOf %in% c("FOBI:0193", "FOBI:0185", "FOODON:00001274", "FOODON:03301702")) %>%
  dplyr::slice(sample(nrow(.), 10, replace = FALSE))

metaboliteList <- fobi_subset %>%
  pull(FOBI)
fobitools::ora(metaboliteList = metaboliteList, 
               metaboliteUniverse = metaboliteUniverse, 
               subOntology = "food", 
               pvalCutoff = 0.01)
className classSize overlap pval padj overlapMetabolites
grapefruit (whole, raw) 14 6 0.0000000 0.0000032 FOBI:030523, FOBI:030320, FOBI:030352, FOBI:050290, FOBI:050030, FOBI:050034
eggplant (whole, raw) 6 4 0.0000016 0.0001163 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
white bread 7 4 0.0000036 0.0001346 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
White fish 7 4 0.0000036 0.0001346 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
white sugar 8 4 0.0000072 0.0001780 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
white wine 8 4 0.0000072 0.0001780 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
Red meat 19 5 0.0000115 0.0002383 FOBI:030320, FOBI:030352, FOBI:030689, FOBI:050030, FOBI:050034
black tea leaf (dry) 9 4 0.0000128 0.0002383 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
kale leaf (raw) 10 4 0.0000212 0.0003502 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
chicory (whole, raw) 4 3 0.0000311 0.0003509 FOBI:030352, FOBI:050030, FOBI:050034
blackberry (whole, raw) 11 4 0.0000330 0.0003509 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
bread food product 11 4 0.0000330 0.0003509 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
cocoa 11 4 0.0000330 0.0003509 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
whole bread 11 4 0.0000330 0.0003509 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
green tea leaf (dry) 12 4 0.0000490 0.0004060 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
red tea 12 4 0.0000490 0.0004060 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
red velvet 12 4 0.0000490 0.0004060 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
rye food product 12 4 0.0000490 0.0004060 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
carrot root (whole, raw) 13 4 0.0000703 0.0004987 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
olive (whole, ripe) 13 4 0.0000703 0.0004987 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
chickpea (whole) 5 3 0.0000770 0.0004987 FOBI:030320, FOBI:050030, FOBI:050034
soybean oil 5 3 0.0000770 0.0004987 FOBI:030320, FOBI:050030, FOBI:050034
turnip (whole, raw) 5 3 0.0000770 0.0004987 FOBI:030352, FOBI:050030, FOBI:050034
grain plant 14 4 0.0000975 0.0005383 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
grain product 14 4 0.0000975 0.0005383 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
lemon (whole, raw) 14 4 0.0000975 0.0005383 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
pear (whole, raw) 14 4 0.0000975 0.0005383 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
cherry (whole, raw) 15 4 0.0001319 0.0006777 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
sweet potato vegetable food product 15 4 0.0001319 0.0006777 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
pomegranate (whole, raw) 6 3 0.0001524 0.0007569 FOBI:030352, FOBI:050030, FOBI:050034
coffee (liquid drink) 17 4 0.0002262 0.0010531 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
oil 17 4 0.0002262 0.0010531 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
banana (whole, ripe) 7 3 0.0002640 0.0011569 FOBI:030352, FOBI:050030, FOBI:050034
pea (whole) 7 3 0.0002640 0.0011569 FOBI:030320, FOBI:050030, FOBI:050034
flour 18 4 0.0002884 0.0011612 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
strawberry (whole, raw) 18 4 0.0002884 0.0011612 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
wine (food product) 18 4 0.0002884 0.0011612 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
tomato (whole, raw) 19 4 0.0003622 0.0014201 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
cauliflower (whole, raw) 8 3 0.0004181 0.0015574 FOBI:030352, FOBI:050030, FOBI:050034
ginger root 8 3 0.0004181 0.0015574 FOBI:030352, FOBI:050030, FOBI:050034
corn (vegetable) food product 2 2 0.0004682 0.0015856 FOBI:050030, FOBI:050034
fruit (dried) 2 2 0.0004682 0.0015856 FOBI:050030, FOBI:050034
papaya (whole, raw) 2 2 0.0004682 0.0015856 FOBI:050030, FOBI:050034
squash (whole, raw) 2 2 0.0004682 0.0015856 FOBI:050030, FOBI:050034
beer 21 4 0.0005499 0.0017811 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
cumin seed (whole, dried) 21 4 0.0005499 0.0017811 FOBI:030320, FOBI:030352, FOBI:050030, FOBI:050034
almond (whole, raw) 9 3 0.0006207 0.0018875 FOBI:030320, FOBI:050030, FOBI:050034
black pepper food product 9 3 0.0006207 0.0018875 FOBI:030320, FOBI:050030, FOBI:050034
tea food product 9 3 0.0006207 0.0018875 FOBI:030352, FOBI:050030, FOBI:050034
wheat 11 3 0.0011945 0.0035595 FOBI:030320, FOBI:050030, FOBI:050034
mango (whole, raw) 3 2 0.0013890 0.0039799 FOBI:050030, FOBI:050034
rhubarb stalk (whole, raw) 3 2 0.0013890 0.0039799 FOBI:050030, FOBI:050034
bean (whole) 12 3 0.0015763 0.0042702 FOBI:030320, FOBI:050030, FOBI:050034
quinoa seed (dried) 12 3 0.0015763 0.0042702 FOBI:030352, FOBI:050030, FOBI:050034
sunflower seed oil 12 3 0.0015763 0.0042702 FOBI:030352, FOBI:050030, FOBI:050034
oregano (ground) 13 3 0.0020281 0.0053961 FOBI:030352, FOBI:050030, FOBI:050034
black currant (whole, raw) 14 3 0.0025546 0.0062966 FOBI:030320, FOBI:050030, FOBI:050034
asparagus (whole, raw) 4 2 0.0027468 0.0062966 FOBI:050030, FOBI:050034
butter 4 2 0.0027468 0.0062966 FOBI:050030, FOBI:050034
lentil (whole) 4 2 0.0027468 0.0062966 FOBI:030320, FOBI:030352
melon (raw) 4 2 0.0027468 0.0062966 FOBI:050030, FOBI:050034
nectarine (whole, raw) 4 2 0.0027468 0.0062966 FOBI:050030, FOBI:050034
pasta 4 2 0.0027468 0.0062966 FOBI:050030, FOBI:050034
peanut butter 4 2 0.0027468 0.0062966 FOBI:050030, FOBI:050034
zucchini plant 4 2 0.0027468 0.0062966 FOBI:050030, FOBI:050034
avocado (whole, raw) 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
bacon food product 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
beetroot 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
Dark yellow vegetables 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
fig (whole) 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
prune food product 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
pumpkin (whole, raw) 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
radish (whole, raw) 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
sauce 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
sauerkraut 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
spinach (whole, raw) 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
stem or spear vegetable 5 2 0.0045267 0.0084310 FOBI:030320, FOBI:030352
watermelon (whole, raw) 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
yogurt (plain) 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
yogurt food product 5 2 0.0045267 0.0084310 FOBI:050030, FOBI:050034
grape (whole, raw) 19 3 0.0064552 0.0112401 FOBI:030352, FOBI:050030, FOBI:050034
barley grain (whole, raw) 6 2 0.0067139 0.0112401 FOBI:050030, FOBI:050034
cucumber (whole, raw) 6 2 0.0067139 0.0112401 FOBI:050030, FOBI:050034
garlic (whole, raw) 6 2 0.0067139 0.0112401 FOBI:050030, FOBI:050034
hazelnut 6 2 0.0067139 0.0112401 FOBI:050030, FOBI:050034
kiwi 6 2 0.0067139 0.0112401 FOBI:050030, FOBI:050034
onion (whole, raw) 6 2 0.0067139 0.0112401 FOBI:050030, FOBI:050034
pineapple (whole, raw) 6 2 0.0067139 0.0112401 FOBI:050030, FOBI:050034
raisin (whole) 6 2 0.0067139 0.0112401 FOBI:050030, FOBI:050034
ale 7 2 0.0092939 0.0137108 FOBI:030320, FOBI:030352
bell pepper 7 2 0.0092939 0.0137108 FOBI:050030, FOBI:050034
broccoli floret (whole, raw) 7 2 0.0092939 0.0137108 FOBI:050030, FOBI:050034
cabbage (whole, raw) 7 2 0.0092939 0.0137108 FOBI:050030, FOBI:050034
celery stalk (raw) 7 2 0.0092939 0.0137108 FOBI:050030, FOBI:050034
cereal 7 2 0.0092939 0.0137108 FOBI:050030, FOBI:050034
cereal food product 7 2 0.0092939 0.0137108 FOBI:050030, FOBI:050034
herb 7 2 0.0092939 0.0137108 FOBI:030320, FOBI:030352
hot pepper vegetable food product 7 2 0.0092939 0.0137108 FOBI:050030, FOBI:050034
vinegar 7 2 0.0092939 0.0137108 FOBI:030320, FOBI:030352
whole oats (raw) 7 2 0.0092939 0.0137108 FOBI:050030, FOBI:050034
yellow bell pepper (whole, raw) 7 2 0.0092939 0.0137108 FOBI:050030, FOBI:050034

Network visualization of metaboliteList terms

Then, with the fobi_graph function we can visualize the metaboliteList terms with their corresponding FOBI relationships.

terms <- fobi_subset %>%
  pull(id_code)

# create the associated graph
fobitools::fobi_graph(terms = terms, 
                      get = "anc",
                      labels = TRUE,
                      legend = TRUE)

Session Information

sessionInfo()
#> R version 4.6.1 (2026-06-24)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 26.04 LTS
#> 
#> Matrix products: default
#> BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.32.so;  LAPACK version 3.12.0
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> time zone: Etc/UTC
#> tzcode source: system (glibc)
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#>  [1] kableExtra_1.4.1 lubridate_1.9.5  forcats_1.0.1    stringr_1.6.0   
#>  [5] dplyr_1.2.1      purrr_1.2.2      readr_2.2.0      tidyr_1.3.2     
#>  [9] tibble_3.3.1     ggplot2_4.0.3    tidyverse_2.0.0  fobitools_1.20.0
#> [13] BiocStyle_2.40.0
#> 
#> loaded via a namespace (and not attached):
#>   [1] DBI_1.3.0              qdapRegex_0.7.10       gridExtra_2.3.1       
#>   [4] rlang_1.3.0            magrittr_2.0.5         otel_0.2.0            
#>   [7] e1071_1.7-17           compiler_4.6.1         RSQLite_3.53.3        
#>  [10] systemfonts_1.3.2      vctrs_0.7.3            pkgconfig_2.0.3       
#>  [13] crayon_1.5.3           fastmap_1.2.0          labeling_0.4.3        
#>  [16] ggraph_2.2.2           rmarkdown_2.31         prodlim_2026.03.11    
#>  [19] tzdb_0.5.0             bit_4.6.0              xfun_0.60             
#>  [22] cachem_1.1.0           jsonlite_2.0.0         blob_1.3.0            
#>  [25] tictoc_1.2.1           BiocParallel_1.46.0    tweenr_2.0.3          
#>  [28] syuzhet_1.0.7          parallel_4.6.1         R6_2.6.1              
#>  [31] bslib_0.11.0           stringi_1.8.7          RColorBrewer_1.1-3    
#>  [34] textclean_0.9.7        parallelly_1.48.0      rpart_4.1.27          
#>  [37] jquerylib_0.1.4        Rcpp_1.1.2             knitr_1.51            
#>  [40] future.apply_1.20.2    clisymbols_1.2.0       timechange_0.4.0      
#>  [43] Matrix_1.7-6           splines_4.6.1          nnet_7.3-20           
#>  [46] igraph_2.3.3           tidyselect_1.2.1       rstudioapi_0.19.0     
#>  [49] yaml_2.3.12            viridis_0.6.5          codetools_0.2-20      
#>  [52] listenv_1.0.0          lattice_0.22-9         withr_3.0.3           
#>  [55] S7_0.2.2               evaluate_1.0.5         ontologyIndex_2.12    
#>  [58] future_1.75.0          survival_3.8-9         proxy_0.4-29          
#>  [61] polyclip_1.10-7        xml2_1.6.0             pillar_1.11.1         
#>  [64] BiocManager_1.30.27    lexicon_1.2.1          generics_0.1.4        
#>  [67] vroom_1.7.1            hms_1.1.4              scales_1.4.0          
#>  [70] ff_4.5.3               globals_0.19.1         xtable_1.8-8          
#>  [73] class_7.3-23           glue_1.8.1             RecordLinkage_0.4-12.6
#>  [76] maketools_1.3.2        tools_4.6.1            sys_3.4.3             
#>  [79] data.table_1.18.4      fgsea_1.38.0           buildtools_1.0.0      
#>  [82] graphlayouts_1.2.5     fastmatch_1.1-8        tidygraph_1.3.1       
#>  [85] cowplot_1.2.0          grid_4.6.1             ipred_0.9-15          
#>  [88] ggforce_0.5.0          cli_3.6.6              evd_2.3-7.1           
#>  [91] textshaping_1.0.5      viridisLite_0.4.3      svglite_2.2.2         
#>  [94] lava_1.9.2             gtable_0.3.6           sass_0.4.10           
#>  [97] digest_0.6.39          ggrepel_0.9.8          farver_2.1.2          
#> [100] memoise_2.0.1          htmltools_0.5.9        lifecycle_1.0.5       
#> [103] bit64_4.8.2            MASS_7.3-66

References

Castellano-Escuder, Pol, Raúl González-Domı́nguez, David S Wishart, Cristina Andrés-Lacueva, and Alex Sánchez-Pla. 2020. “FOBI: An Ontology to Represent Food Intake Data and Associate It with Metabolomic Data.” Database 2020.