Standartox

Standartox is a database and tool facilitating the retrieval of ecotoxicological test data. It is based on the EPA ECOTOX database as well as on data from several other chemical databases and allows users to filter and aggregate ecotoxicological test data in an easy way. It can be accessed via this R-package standartox. Ecotoxicological test data is used in environmental risk assessment to calculate effect measures such as TU - Toxic Units or SSD - Species Sensitivity Distributions to asses environmental toxicity of chemicals.

Installation

# install.packages('standartox') # CRAN Server version
remotes::install_github('andschar/standartox') # Github version

Functions

Standartox mainly consists of the functions stx_catalog() and stx_query(). The former allows you to retrieve a summary catalog of the data. The latter querries and aggregates the data from the database. There are also stx_data(), stx_chem(), stx_taxa() and stx_meta() funcitons which fetch the whole toxicity, chemical, taxonomic and meta data tables respectively.

stx_catalog()

The function returns a list of all possible arguments that can bes use in stx_query().

require(standartox)
require(data.table)
catal = stx_catalog()
names(catal)

##  [1] "cas"                     "casnr"                   "chem_class"              "chem_name"              
##  [5] "ref_author"              "ref_number"              "ref_title"               "ref_year"               
##  [9] "tax_class"               "tax_continent"           "tax_family"              "tax_genus"              
## [13] "tax_group"               "tax_habitat"             "tax_order"               "tax_rank"               
## [17] "tax_taxon"               "casnr"                   "cl_id"                   "concentration"          
## [21] "concentration_orig"      "concentration_type"      "concentration_unit"      "concentration_unit_orig"
## [25] "duration"                "duration_orig"           "duration_unit"           "duration_unit_orig"     
## [29] "effect"                  "endpoint"                "endpoint_group"          "exposure"               
## [33] "measurement"             "organism_lifestage"      "qualifier"               "ref_number"             
## [37] "result_id"               "tl_id"

catal$endpoint # access the parameter top five endpoints

Showing the top 10 endpoint values from stx_catalog()

n	variable
205080	NOEL
196597	NR
165693	LOEL
165146	NOEC
143740	LC50
123889	LOEC
56362	EC50
22496	BCF
17739	NR-LETH
16213	LD50

stx_query()

The function allows you to query and filter the standartox data base.

The most basic function call will return a data table filtered with default settings: endpoint_group = c("XX50", "NOEX", "LOEX") and duration_unit = "h".

By setting verbose = TRUE the user can follow all the query steps in more detail.

## Querying Standartox data base ...

## Reading in Standartox Data ...

## Removing rows with 'NR' (not reported) for endpoint & duration_unit ...

## Appending chemical information ...

## Appending taxonomic information ...

## Query returned 801451 results out of 1212683 total entries.
## Done!

Example: Oncorhynchus

Let’s say, we want to retrieve the 20 most tested chemicals on the genus Oncorhynchus. We allow for test durations between 48 and 120 hours and want the tests restricted to active ingredients only. Since we are only interested in the half maximal effective concentration, we choose XX50 as our endpoint. As an aggregation method we choose the geometric mean. The code below makes use of the data.table package.

# Run query
oncor = stx_query(
  tax_genus = 'Oncorhynchus',
  endpoint_group = 'XX50',
  concentration_unit = 'g/l',
  effect = 'mortality',
  duration = c(48, 120),
  concentration_type = 'active ingredient',
  verbose = TRUE
)

## Querying Standartox data base ...

## Reading in Standartox Data ...

## Removing rows with 'NR' (not reported) for endpoint & duration_unit ...

## Appending chemical information ...

## Appending taxonomic information ...

## Query returned 3178 results out of 1212683 total entries.
## Done!

We subset the retrieved data to the 20 most tested chemicals and plot the result.

cas20 = oncor[ , .N, cas ][ order(-N) ][1:20]
oncor20 = oncor[ cas %in% cas20$cas ]
# add new column which combines common_name & cas
oncor20[ , new_chem_name := paste0(common_name, ' [CAS: ', cas, ']') ]
gmn_dt = oncor20[ , .(gmn = exp(mean(log(concentration), na.rm = TRUE))), .(cas, new_chem_name, tax_genus)]

require(ggplot2)
ggplot(oncor20, aes(y = new_chem_name)) +
  geom_point(aes(x = concentration, col = 'All values'),
             pch = 1, alpha = 0.3) +
  geom_point(data = gmn_dt,
             aes(y = reorder(new_chem_name, -gmn), x = gmn, col = 'Standartox value\n(Geometric mean)'),
             size = 3) +
  scale_x_log10(breaks = c(0.01, 0.1, 1, 10, 100, 1000, 10000),
                labels = c(0.01, 0.1, 1, 10, 100, 1000, 10000)) +
  scale_color_viridis_d(name = '') +
  labs(title = 'LC50 values for Genus: Oncorhynchus',
       subtitle = '20 most tested chemicals',
       x = 'Concentration [g/L]') +
  theme_minimal() +
  theme(axis.title.y = element_blank())

Article

The article on Standartox is published here.

Contributors

Want to contribute?

Check out our contribution guide here.

Meta

• Please report any issues, bugs or feature requests
• License: MIT
• Get citation information for the standartox package in R doing citation(package = 'standartox')