| Title: | Exclusion-Based Parentage Assignment Using Multilocus Genotype Data |
| Version: | 0.1.0 |
| Description: | Exclusion-based parentage assignment is essential for studies in biodiversity conservation and breeding programs - Kang Huang, Rui Mi, Derek W Dunn, Tongcheng Wang, Baoguo Li, (2018), <doi:10.1534/genetics.118.301592>. The tool compares multilocus genotype data of potential parents and offspring, identifying likely parentage relationships while accounting for genotyping errors, missing data, and duplicate genotypes. 'acoRn' includes two algorithms: one generates synthetic genotype data based on user-defined parameters, while the other analyzes existing genotype data to identify parentage patterns. The package is versatile, applicable to diverse organisms, and offers clear visual outputs, making it a valuable resource for researchers. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2 |
| Imports: | data.table, stringr, stringi |
| Depends: | R (≥ 2.10) |
| LazyData: | true |
| Suggests: | testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2024-10-01 09:03:08 UTC; nikospech |
| Author: | Nikos Pechlivanis 
[aut, cre],
Fotis Psomopoulos
[aut],
Aristotelis Papageorgiou
[aut] |
| Maintainer: | Nikos Pechlivanis <npechlv@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2024-10-02 14:00:02 UTC |
acoRn workflow
Description
acoRn workflow
Usage
acoRn(adults, progeny)
Arguments
adults |
a data.frame |
progeny |
a data.frame |
Value
a data.frame
Title
Description
Title
Usage
clean_input(genotypes)
Arguments
genotypes |
data.table |
Value
data.table
Title
Description
Title
Usage
create_mock_parents(nmarkers = 10, ntrees = 100, nvariants = 4, maf = NULL)
Arguments
nmarkers |
number of markers |
ntrees |
number of trees |
nvariants |
number of trees |
maf |
minimum allele frequency |
Value
a list
Title
Description
Title
Usage
create_mock_progeny(info, fparents, mparents, prog)
Arguments
info |
mock parents, as generated from |
fparents |
number of female parents |
mparents |
number of male parents |
prog |
number of progeny?? |
Value
a data table
Report duplicates
Description
Report duplicates
Usage
exclude_duplicates(parents, adults = NULL, progeny = NULL)
Arguments
parents |
a data.frame |
adults |
a data.frame |
progeny |
a data.frame |
Value
a data.frame
Identify relationships between parents and progenies
Description
Identify relationships between parents and progenies
Usage
find_parents(adults, progeny)
Arguments
adults |
a data.frame containing |
progeny |
a data.frame |
Value
a data.frame
Identify duplicates in genotypes (i.e. parents or progenies)
Description
Identify duplicates in genotypes (i.e. parents or progenies)
Usage
identify_duplicates(genotypes, abbr = NULL)
Arguments
genotypes |
a data.frame with the genotypes |
abbr |
a string with abbreviation to use |
Value
a data.frame
Tree progeny data set
Description
An example of tree progeny data set
Usage
offspring
Format
offspring
A data frame with 7,240 rows and 60 columns:
- country
Country name
- iso2, iso3
2 & 3 letter ISO country codes
- year
Year
...
Source
https://www.who.int/teams/global-tuberculosis-programme/data
Tree parents data set
Description
An example of tree parents data set
Usage
parents
Format
parents
A data frame with 7,240 rows and 60 columns:
- country
Country name
- iso2, iso3
2 & 3 letter ISO country codes
- year
Year
...
Source
https://www.who.int/teams/global-tuberculosis-programme/data