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72 lines
1.7 KiB
Plaintext
72 lines
1.7 KiB
Plaintext
---
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title: "AMR Goes Vet"
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author: "Jason, Matthew, Javier, Matthijs"
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date: "2024-02-20"
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format:
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html:
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embed-resources: true
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---
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## Import WHONET data set
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```{r, message=FALSE, warning=FALSE}
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library(dplyr)
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library(readr)
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library(tidyr)
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library(janitor)
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# WHONET version of 16th Feb 2024
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whonet_breakpoints <- read_tsv("WHONET/Resources/Breakpoints.txt", na = c("", "NA", "-"),
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show_col_types = FALSE, guess_max = Inf) %>%
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filter(GUIDELINES %in% c("CLSI", "EUCAST"))
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dim(whonet_breakpoints)
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```
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# EDA of Animal Breakpoints
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```{r}
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whonet_breakpoints |>
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filter(BREAKPOINT_TYPE != "Human")
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whonet_breakpoints |>
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filter(BREAKPOINT_TYPE != "Human") |>
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count(BREAKPOINT_TYPE)
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whonet_breakpoints |>
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filter(BREAKPOINT_TYPE == "Animal")
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```
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### Count of all animal breakpoints
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```{r}
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whonet_breakpoints |>
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filter(BREAKPOINT_TYPE == "Animal") |>
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count(YEAR, HOST, REFERENCE_TABLE = gsub("VET[0-9]+ ", "", REFERENCE_TABLE)) |>
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pivot_wider(names_from = YEAR, values_from = n, values_fill = list(n = 0)) |>
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arrange(HOST, REFERENCE_TABLE) |>
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adorn_totals(name = "TOTAL")
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```
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### Cats only
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```{r}
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whonet_breakpoints |>
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filter(HOST == "Cats", YEAR >= 2021) |>
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select(GUIDELINES, YEAR, TEST_METHOD, ORGANISM_CODE, R, S) |>
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mutate(MO_NAME = AMR::mo_shortname(ORGANISM_CODE), .before = R) |>
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as.data.frame()
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```
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### Site of infection in cats (2023)
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```{r}
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whonet_breakpoints |>
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filter(HOST == "Cats", YEAR == 2023) |>
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mutate(MO = AMR::mo_shortname(ORGANISM_CODE),
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AB = AMR::ab_name(WHONET_ABX_CODE),
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SITE_OF_INFECTION = substr(SITE_OF_INFECTION, 1, 25)) |>
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arrange(MO, AB) |>
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select(MO, AB, SITE_OF_INFECTION) |>
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as.data.frame()
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```
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