2022
DOI: 10.1093/g3journal/jkac219
|View full text |Cite
|
Sign up to set email alerts
|

stuart: an R package for the curation of SNP genotypes from experimental crosses

Abstract: Genetic mapping in two-generation crosses requires genotyping, usually performed with SNP markers arrays which provide high-density genetic information. However, genetic analysis on raw genotypes can lead to spurious or unreliable results due to defective SNP assays or wrong genotype interpretation. Here we introduce stuart, an open-source R package which analyzes raw genotyping data to filter SNP markers based on informativeness, Mendelian inheritance pattern and consistency with parental genotypes. Functions… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
3
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
3
2

Relationship

1
4

Authors

Journals

citations
Cited by 6 publications
(3 citation statements)
references
References 15 publications
0
3
0
Order By: Relevance
“…Raw genotypes were curated using the stuart package [ 45 ]. QTL mapping was performed using R/qtl [ 46 ].…”
Section: Methodsmentioning
confidence: 99%
“…Raw genotypes were curated using the stuart package [ 45 ]. QTL mapping was performed using R/qtl [ 46 ].…”
Section: Methodsmentioning
confidence: 99%
“…Raw genotypes were curated using the stuart package (43). QTL mapping was performed using R/qtl (44).…”
Section: Methodsmentioning
confidence: 99%
“…Genotyping arrays have been a staple in mouse research for more than two decades and have been successfully adopted for genetic QC and colony maintenance (Petkov et al 2004; Yang et al 2011; Morgan et al 2015; Andrews et al 2021; Amos-Landgraf et al 2022). Five years after its introduction, the MiniMUGA array has been used for genotyping over 40,000 mouse samples and the manuscript describing the array and its capabilities has been cited widely (Sigmon et al 2020; Birling et al 2022; Bourdon and Montagutelli 2022; Yoshiki et al 2022; Smith et al 2022). Part of MiniMUGA’s success is due to its unique characteristics, including discrimination between commercial substrains, robust chromosomal sex determination, and detection of commonly used constructs.…”
Section: Introductionmentioning
confidence: 99%