The website of qpdt is available under https://fbzwsqualitasag.github.io/qpdt/
The goal of qpdt is to provide a package with generic pedigree tools used at Qualitas AG.
You can install the development version from GitHub with:
# install.packages("devtools") devtools::install_github("fbzwsqualitasag/qpdt")
This is a basic example which shows you how basic properties of a pedigree can be checked:
library(qpdt) ## basic example code s_pedigree <- system.file('extdata', 'PopReport_SN_ohne_20210115.csv_adaptfin2.csv', package = 'qprppedigree') check_pedig_parent(ps_pedig_path = s_pedigree) #> Warning: `guess_max` is a very large value, setting to `21474836` to avoid #> exhausting memory #> Parsed with column specification: #> cols( #> `#IDTier` = col_double(), #> IDVater = col_double(), #> IDMutter = col_double(), #> Birthdate = col_date(format = ""), #> Geschlecht = col_character(), #> PLZ = col_double(), #> introg = col_double(), #> inb_gen = col_logical(), #> cryo = col_double() #> ) #> $PedFile #> [1] "/Library/Frameworks/R.framework/Versions/4.0/Resources/library/qprppedigree/extdata/PopReport_SN_ohne_20210115.csv_adaptfin2.csv" #> #> $NrMissingSire #> [1] 1211 #> #> $NrMissingDam #> [1] 462 #> #> $NrSireNotAnimal #> [1] 4243 #> #> $NrDamNotAnimal #> [1] 6468 #> #> $TblSireBdate #> # A tibble: 9 x 4 #> `#IDTier` IDVater `Birthdate.#IDTier` Birthdate.IDVater #> <dbl> <dbl> <date> <date> #> 1 1000810031 1000050624 2013-03-09 2013-05-02 #> 2 999870937 1000161006 2013-03-20 2013-10-08 #> 3 1000810027 1000050624 2013-03-25 2013-05-02 #> 4 1000813707 1000050624 2013-03-26 2013-05-02 #> 5 1000810038 1000050624 2013-03-26 2013-05-02 #> 6 1000810020 1000050624 2013-04-15 2013-05-02 #> 7 1000711443 1000050624 2013-04-15 2013-05-02 #> 8 1000456126 1005609568 2013-11-26 2016-02-02 #> 9 1004653188 1005845648 2015-03-07 2016-09-29 #> #> $TblDamBdate #> # A tibble: 2 x 4 #> `#IDTier` IDMutter `Birthdate.#IDTier` Birthdate.IDMutter #> <dbl> <dbl> <date> <date> #> 1 99768 99765 1983-03-20 1985-02-26 #> 2 1000878464 1004910666 2015-03-05 2015-10-12 #> #> $TblSireEqID #> # A tibble: 0 x 9 #> # … with 9 variables: `#IDTier` <dbl>, IDVater <dbl>, IDMutter <dbl>, #> # Birthdate <date>, Geschlecht <chr>, PLZ <dbl>, introg <dbl>, inb_gen <lgl>, #> # cryo <dbl> #> #> $TblDamEqID #> # A tibble: 1 x 9 #> `#IDTier` IDVater IDMutter Birthdate Geschlecht PLZ introg inb_gen cryo #> <dbl> <dbl> <dbl> <date> <chr> <dbl> <dbl> <lgl> <dbl> #> 1 1004866450 9.99e8 1.00e9 2011-03-27 F 7411 0 NA 0 #> #> $TblSireWrongSex #> # A tibble: 3 x 2 #> IDVater Geschlecht #> <dbl> <chr> #> 1 1007737726 F #> 2 1006000916 F #> 3 1004668293 F #> #> $TblDamWrongSex #> # A tibble: 0 x 2 #> # … with 2 variables: IDMutter <dbl>, Geschlecht <chr>
If you want to find whether a certain pedigree contains cycles the following statements provides an anser.
s_pedi_path <- system.file('extdata','data_sample2.csv', package = 'qprppedigree') check_cycle_pedigree(ps_pedig_path = s_pedi_path) #> Parsed with column specification: #> cols( #> `#animal` = col_double(), #> sire = col_double(), #> dam = col_double(), #> birth_date = col_date(format = ""), #> sex = col_character(), #> plz = col_double(), #> introg = col_double(), #> inb_gen = col_logical(), #> cryo = col_logical() #> ) #> $PedFile #> [1] "/Library/Frameworks/R.framework/Versions/4.0/Resources/library/qprppedigree/extdata/data_sample2.csv" #> #> $HasCycle #> [1] FALSE
Latest Changes: 2021-03-26 09:27:55 (pvr)