Harness information from the US EPA ECOTOXicology Knowledgebase
ECOTOXr can be used to explore and analyse data from the US EPA
ECOTOX database. More specifically you
can:
- Build a local SQLite copy of the US EPA ECOTOX database
- Search and extract data from the local database
- Use experimental features to search the on-line dashboards: ECOTOX and CompTox
The ECOTOXr package allows you to search and extract data from the
ECOTOXicological Knowledgebase and
import it directly into R. This will allow you to formalize and
document the search- and extract-procedures in R code. This makes it
easier to share and reproduce such procedures and its results. Moreover,
you can directly apply any statistical analysis offered in R.
Get CRAN version
install.packages("ECOTOXr")Get development version from r-universe
install.packages("ECOTOXr", repos = c("https://pepijn-devries.r-universe.dev", "https://cloud.r-project.org"))Although ECOTOXr has experimental features to search the on-line
database. The package will reach its full potential when you build a
copy of the database on your local machine.
Download and build a local copy of the latest ASCII export of the US EPA ECOTOX database
download_ecotox_data()Obviously, searching the local database is only possible after the download and build is ready (see previous section).
Search the local database for tests of water flea Daphnia magna exposed to benzene
search_ecotox(
list(
latin_name = list(terms = "Daphnia magna", method = "exact"),
chemical_name = list(terms = "benzene", method = "exact")
)
)Let’s have a look at 3 different approaches for retrieving a specific
record from the local database, using the unique identifier result_id.
The first option is to use the build in search_ecotox function. It
uses simple R syntax and allows you to search and collect any field
from any table in the database. Furthermore, all requested output fields
are automatically joined to the result without the end-user needing to
know anything about the database structure.
Using the prefab function
search_ecotoxpackaged byECOTOXr
search_ecotox(
list(
result_id = list(terms = "401386", method = "exact")
),
as_data_frame = F
)
#> 'dose_responses.response_site' was renamed 'dose_link_response_site'
#> 'chemicals.cas_number' was renamed 'test_cas'
#> 'chemicals.chemical_name' was renamed 'test_chemical'
#> 'dose_responses.dose_resp_id' was renamed 'dose_link_dose_resp_id'
#> # A tibble: 1 × 98
#> test_cas test_grade test_grade_comments test_purity_mean_op test_purity_mean
#> * <int> <chr> <chr> <chr> <chr>
#> 1 71432 NR "" "" NR
#> # ℹ 93 more variables: test_purity_min_op <chr>, test_purity_min <chr>,
#> # test_purity_max_op <chr>, test_purity_max <chr>,
#> # test_purity_comments <chr>, organism_lifestage <chr>,
#> # organism_age_mean_op <chr>, organism_age_mean <chr>,
#> # organism_age_min_op <chr>, organism_age_min <chr>,
#> # organism_age_max_op <chr>, organism_age_max <chr>,
#> # exposure_duration_mean_op <chr>, exposure_duration_mean <chr>, …If you like to use dplyr verbs, you
are in luck. SQLite database can be approached using dplyr verbs. This
approach will only return information from the results table. The
end-user will have to join other information (like test species and test
substance) manually. This does require knowledge of the database
structure.
Using
dplyrverbs
con <- dbConnectEcotox()
dplyr::tbl(con, "results") |>
dplyr::filter(result_id == "401386") |>
dplyr::collect()
#> # A tibble: 1 × 137
#> result_id test_id sample_size_mean_op sample_size_mean sample_size_min_op
#> <int> <int> <chr> <chr> <chr>
#> 1 401386 1020021 "" NC ""
#> # ℹ 132 more variables: sample_size_min <chr>, sample_size_max_op <chr>,
#> # sample_size_max <chr>, sample_size_unit <chr>, sample_size_comments <chr>,
#> # obs_duration_mean_op <chr>, obs_duration_mean <chr>,
#> # obs_duration_min_op <chr>, obs_duration_min <chr>,
#> # obs_duration_max_op <chr>, obs_duration_max <chr>, obs_duration_unit <chr>,
#> # obs_duration_comments <chr>, endpoint <chr>, endpoint_comments <chr>,
#> # trend <chr>, effect <chr>, effect_comments <chr>, measurement <chr>, …If you prefer working using SQL directly, that is fine too. The
RSQLite package allows
you to get queries using SQL statements. The result is identical to
that of the previous approach. Here too the end-user needs knowledge of
the database structure in order to join additional data.
Using
SQLsyntax
dbGetQuery(con, "SELECT * FROM results WHERE result_id='401386'") |>
dplyr::as_tibble()
#> # A tibble: 1 × 137
#> result_id test_id sample_size_mean_op sample_size_mean sample_size_min_op
#> <int> <int> <chr> <chr> <chr>
#> 1 401386 1020021 "" NC ""
#> # ℹ 132 more variables: sample_size_min <chr>, sample_size_max_op <chr>,
#> # sample_size_max <chr>, sample_size_unit <chr>, sample_size_comments <chr>,
#> # obs_duration_mean_op <chr>, obs_duration_mean <chr>,
#> # obs_duration_min_op <chr>, obs_duration_min <chr>,
#> # obs_duration_max_op <chr>, obs_duration_max <chr>, obs_duration_unit <chr>,
#> # obs_duration_comments <chr>, endpoint <chr>, endpoint_comments <chr>,
#> # trend <chr>, effect <chr>, effect_comments <chr>, measurement <chr>, …It is the end-users own responsibility to check the quality of collected data, using the original referenced source in order to evaluate its fitness for use, see also: https://cfpub.epa.gov/ecotox/help.cfm#info-limitations.
Note that the package maintainer is not affiliated with the US EPA, this package is therefore not official US EPA software.
- De Vries, P. (2024) ECOTOXr: An R package for reproducible and transparent retrieval of data from EPA’s ECOTOX database. Chemosphere 364 143078 https://doi.org/10.1016/j.chemosphere.2024.143078
- Manual of the CRAN release
- EPA ECOTOX help https://cfpub.epa.gov/ecotox/help.cfm
- Olker, Jennifer H.; Elonen, Colleen M.; Pilli, Anne; Anderson, Arne; Kinziger, Brian; Erickson, Stephen; Skopinski, Michael; Pomplun, Anita; LaLone, Carlie A.; Russom, Christine L.; Hoff, Dale. (2022): The ECOTOXicology Knowledgebase: A Curated Database of Ecologically Relevant Toxicity Tests to Support Environmental Research and Risk Assessment. Environmental Toxicology and Chemistry 41(6) 1520-1539 https://doi.org/10.1002/etc.5324