,
Fotis Psomopoulos [aut] ,
Aristotelis Papageorgiou [aut]
| Title: | Exclusion-Based Parentage Assignment Using Multilocus Genotype Data |
|---|---|
| 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. |
| Authors: | Nikos Pechlivanis [aut, cre] ,
Fotis Psomopoulos [aut] ,
Aristotelis Papageorgiou [aut]
|
| Maintainer: | Nikos Pechlivanis <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.1.0 |
| Built: | 2024-11-03 04:50:37 UTC |
| Source: | https://github.com/npechl/acorn |
acoRn workflow
acoRn(adults, progeny)acoRn(adults, progeny)
adults |
a data.frame |
progeny |
a data.frame |
a data.frame
Title
clean_input(genotypes)clean_input(genotypes)
genotypes |
data.table |
data.table
Title
create_mock_parents(nmarkers = 10, ntrees = 100, nvariants = 4, maf = NULL)create_mock_parents(nmarkers = 10, ntrees = 100, nvariants = 4, maf = NULL)
nmarkers |
number of markers |
ntrees |
number of trees |
nvariants |
number of trees |
maf |
minimum allele frequency |
a list
Title
create_mock_progeny(info, fparents, mparents, prog)create_mock_progeny(info, fparents, mparents, prog)
info |
mock parents, as generated from |
fparents |
number of female parents |
mparents |
number of male parents |
prog |
number of progeny?? |
a data table
Report duplicates
exclude_duplicates(parents, adults = NULL, progeny = NULL)exclude_duplicates(parents, adults = NULL, progeny = NULL)
parents |
a data.frame |
adults |
a data.frame |
progeny |
a data.frame |
a data.frame
Identify relationships between parents and progenies
find_parents(adults, progeny)find_parents(adults, progeny)
adults |
a data.frame containing |
progeny |
a data.frame |
a data.frame
Identify duplicates in genotypes (i.e. parents or progenies)
identify_duplicates(genotypes, abbr = NULL)identify_duplicates(genotypes, abbr = NULL)
genotypes |
a data.frame with the genotypes |
abbr |
a string with abbreviation to use |
a data.frame
An example of tree progeny data set
offspringoffspring
offspringA data frame with 7,240 rows and 60 columns:
Country name
2 & 3 letter ISO country codes
Year
...
https://www.who.int/teams/global-tuberculosis-programme/data
An example of tree parents data set
parentsparents
parentsA data frame with 7,240 rows and 60 columns:
Country name
2 & 3 letter ISO country codes
Year
...
https://www.who.int/teams/global-tuberculosis-programme/data