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New mo algorithm, prepare for 2.0
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Dr. Matthijs Berends
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@ -115,7 +115,7 @@ All reference data (about microorganisms, antibiotics, R/SI interpretation, EUCA
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On this page, we explain how to download them and how the structure of the data sets look like.
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## `microorganisms`: Microbial Taxonomy (currently accepted names)
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## `microorganisms`: Full Microbial Taxonomy
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`r structure_txt(microorganisms)`
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@ -127,11 +127,11 @@ This data set is in R available as `microorganisms`, after you load the `AMR` pa
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### Source
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Our full taxonomy of microorganisms is based on the authoritative and comprehensive:
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This data set contains the full microbial taxonomy of `r nr2char(length(unique(AMR::microorganisms$kingdom[!AMR::microorganisms$kingdom %like% "unknown"])))` kingdoms from the List of Prokaryotic names with Standing in Nomenclature (LPSN) and the Global Biodiversity Information Facility (GBIF):
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* [Catalogue of Life](http://www.catalogueoflife.org) (included version: `r AMR:::CATALOGUE_OF_LIFE$year`)
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* [List of Prokaryotic names with Standing in Nomenclature](https://lpsn.dsmz.de) (LPSN, last updated: `r AMR:::CATALOGUE_OF_LIFE$yearmonth_LPSN`)
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* `r AMR:::SNOMED_VERSION$current_source`, retrieved from the [`r AMR:::SNOMED_VERSION$title`](`r AMR:::SNOMED_VERSION$url`), OID `r AMR:::SNOMED_VERSION$current_oid`, version `r AMR:::SNOMED_VERSION$current_version`
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* `r AMR:::TAXONOMY_VERSION$LPSN$citation` Accessed from <`r AMR:::TAXONOMY_VERSION$LPSN$url`> on `r documentation_date(AMR:::TAXONOMY_VERSION$LPSN$accessed_date)`.
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* `r AMR:::TAXONOMY_VERSION$GBIF$citation` Accessed from <`r AMR:::TAXONOMY_VERSION$GBIF$url`> on `r documentation_date(AMR:::TAXONOMY_VERSION$GBIF$accessed_date)`.
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* `r AMR:::TAXONOMY_VERSION$SNOMED$citation` URL: <`r AMR:::TAXONOMY_VERSION$SNOMED$url`>
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### Example content
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@ -153,33 +153,6 @@ microorganisms %>%
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print_df()
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```
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## `microorganisms.old`: Microbial Taxonomy (previously accepted names)
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`r structure_txt(microorganisms.old)`
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**Note:** remember that the 'ref' columns contains the scientific reference to the old taxonomic entries, i.e. of column *'fullname'*. For the scientific reference of the new names, i.e. of column *'fullname_new'*, see the `microorganisms` data set.
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This data set is in R available as `microorganisms.old`, after you load the `AMR` package.
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`r download_txt("microorganisms.old")`
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### Source
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This data set contains old, previously accepted taxonomic names. The data sources are the same as the `microorganisms` data set:
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* [Catalogue of Life](http://www.catalogueoflife.org) (included version: `r AMR:::CATALOGUE_OF_LIFE$year`)
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* [List of Prokaryotic names with Standing in Nomenclature](https://lpsn.dsmz.de) (LPSN, last updated: `r AMR:::CATALOGUE_OF_LIFE$yearmonth_LPSN`)
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### Example content
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Example rows when filtering on *Escherichia*:
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```{r, echo = FALSE}
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microorganisms.old %>%
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filter(fullname %like% "^Escherichia") %>%
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print_df()
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```
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## `antibiotics`: Antibiotic Agents
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@ -28,6 +28,8 @@ Note: to keep the package size as small as possible, we only included this vigne
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The `AMR` package is a [free and open-source](https://msberends.github.io/AMR/#copyright) R package with [zero dependencies](https://en.wikipedia.org/wiki/Dependency_hell) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.
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This work was published in the Journal of Statistical Software (Volume 104(3); [DOI 10.18637/jss.v104.i03](https://doi.org/10.18637/jss.v104.i03)) and formed the basis of two PhD theses ([DOI 10.33612/diss.177417131](https://doi.org/10.33612/diss.177417131) and [DOI 10.33612/diss.192486375](https://doi.org/10.33612/diss.192486375)).
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After installing this package, R knows `r AMR:::format_included_data_number(AMR::microorganisms)` distinct microbial species and all `r AMR:::format_included_data_number(rbind(AMR::antibiotics[, "atc", drop = FALSE], AMR::antivirals[, "atc", drop = FALSE]))` antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.
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The `AMR` package is available in English, Chinese, Danish, Dutch, French, German, Greek, Italian, Japanese, Polish, Portuguese, Russian, Spanish, Swedish, Turkish and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
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@ -36,7 +38,7 @@ This package is fully independent of any other R package and works on Windows, m
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This package can be used for:
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* Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the Catalogue of Life and List of Prokaryotic names with Standing in Nomenclature
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* Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the List of Prokaryotic names with Standing in Nomenclature (LPSN) and the Global Biodiversity Information Facility (GBIF)
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* Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines
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* Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records
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* Determining first isolates to be used for AMR data analysis
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@ -55,7 +57,7 @@ This package can be used for:
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All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this `AMR` package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find [all download links on our website](https://msberends.github.io/AMR/articles/datasets.html), which is automatically updated with every code change.
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This R package was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl), in collaboration with non-profit organisations [Certe Medical Diagnostics and Advice Foundation](https://www.certe.nl) and [University Medical Center Groningen](https://www.umcg.nl). This R package formed the basis of two PhD theses ([DOI 10.33612/diss.177417131](https://doi.org/10.33612/diss.177417131) and [DOI 10.33612/diss.192486375](https://doi.org/10.33612/diss.192486375)) but is actively and durably maintained (see [changelog)](https://msberends.github.io/AMR/news/index.html)) by two public healthcare organisations in the Netherlands.
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This R package was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl), in collaboration with non-profit organisations [Certe Medical Diagnostics and Advice Foundation](https://www.certe.nl) and [University Medical Center Groningen](https://www.umcg.nl), and is being [actively and durably maintained](./news) by two public healthcare organisations in the Netherlands.
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----
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