README
R. Mark Sharp 03/28/2021
nprcgenekeepr – Version 1.0.5 (20210322)
Introduction
The goal of nprcgenekeepr is to implement Genetic Tools for Colony Management. It was initially conceived and developed as a Shiny web application at the Oregon National Primate Research Center (ONPRC) to facilitate some of the analyses they perform regularly. It has been enhanced to have more capability as a Shiny application and to expose the functions so they can be used either interactively or in R scripts.
This work has been supported in part by NIH grants P51 RR13986 to the Southwest National Primate Research Center and P51 OD011092 to the Oregon National Primate Research Center.
At present, the application supports 5 functions:
- Quality control of studbooks contained in text files or Excel workbooks and of pedigrees within LabKey Electronic Health Records (EHR)
- Creation of pedigrees from a lists of animals using the LabKey EHR integration
- Creation and display of an age by sex pyramid plot of the living animals within the designated pedigree
- Generation of Genetic Value Analysis Reports
- Creation of potential breeding groups with and without proscribed sex ratios and defined maximum kinships.
For more information see:
A Practical Approach for Designing Breeding Groups to Maximize Genetic
Diversity in a Large Colony of Captive Rhesus Macaques (Macaca
mulatto) Vinson, A ; Raboin, MJ Journal Of The American Association
For Laboratory Animal Science, 2015 Nov, Vol.54(6), pp.700-707 [Peer
Reviewed Journal]
Installation
You can install the development version of nprcgenekeepr from GitHub from the R console prompt with:
install.packages("devtools")
devtools::install_github("rmsharp/nprcgenekeepr")All missing dependencies should be automatically installed.
Online Documentation
You can find the complete online documentation at https://rmsharp.github.io/nprcgenekeepr/.
At the top of the page are three menus to the right of the Home icon:
Reference, Articles, and Changelog.
The Reference menu at the top of the page brings up the list of
documentation for Data objects, Major Features and Functions,
Primary interactive functions and All exposed functions.
The Articles menu brings up the list of vignettes, which are, except
for Development Plans, tutorials for using the package.
The Changelog brings up a copy of the NEWS file of the package, which
records the major changes made for each version.
Running Shiny Application
The toolset available within nprcgenekeepr can be used inside standard R scripts. However, it was originally designed to be used within a Shiny application that can be started with:
library(nprcgenekeepr)
runGeneKeepR()Summary of Major Functions
Quality Control
Studbooks maintained by breeding colonies generally contain information of varying quality. The quality control functions of the toolkit check to ensure all animals listed as parents have their own line entries, all parents have the appropriate sex listed, no animals are listed as both a sire and a dam, duplicate entries are removed, pedigree generation numbers are added, and all dates are valid dates. In addition, exit dates are added if possible and are consistent with other information such as departure dates and death dates. Current ages of animals that are still alive are added if a database connection is provided via a configuration file and the user has read permission on a LabKey server with the demographic data in an EHR (Electronic Health Record) module. See
Parents with ages below a user selected threshold are identified. A minimum parent age in years is set by the user and is used to ensure each parent is at least that age on the birth date of an offspring. The minimum parent age defaults to 2 years. This check is not performed for animals with missing birth dates.
Creation of Pedigree From a List of Potential Breeders and LabKey Integration
The user can enter a list of focal animals in a CSV file that will be used to create a pedigree containing all direct relative (ancestors and descendants) via the labkey.selectRows function within the Rlabkey package if a database connection is provided via a configuration file and the user has read permission on a LabKey server with the demographic data in an EHR (Electronic Health Record) module.
Two configuration files are needed to use the database features of nprcgenekeepr with LabKey. The first file is named _netrc on Microsoft Windows operating systems and .netrc otherwise, allows the user to authenticate with LabKey through the LabKey API and is fully described by LabKey documentation
The second file is named _nprcgenekeepr_config on Microsoft
Windows operating systems and .nprcgenekeepr_config otherwise and
is the nprcgenekeepr configuration
file
An image of this example configuration file is included as a data object
and can be loaded and viewed with the following lines of R code in the R
console.
data("exampleNprcgenekeeprConfig")
View(exampleNprcgenekeeprConfig)Display of an age by sex pyramid plot
Adapted from on 20190603. Written by Matt Rosenberg. Updated May 07, 2019
The most important demographic characteristic of a population is its age-sex structure. Age-sex pyramids (also known as population pyramids) graphically display this information to improve understanding and make comparison easy. The population pyramid sometimes has a distinctive pyramid-like shape when displaying a growing population.
How to Read the Age-Sex Graph
An age-sex pyramid breaks down a population into male and female genders and age ranges. Usually, you’ll find the left side of the pyramid graphing the male population and the right side of the pyramid displaying the female population.
Along the horizontal axis (x-axis) of a population pyramid, the graph displays the population either as a total population of that age or as a percentage of the population at that age. The center of the pyramid starts at zero population and extends out to the left for males and right for females in increasing size, or proportion of the population.
Along the vertical axis (y-axis), age-sex pyramids display two-year age increments, from birth at the bottom to old age at the top.
Genetic Value Analysis Reports
The Genetic Value Analysis is a ranking scheme developed at ONPRC to indicate the relative breeding value of animals in the colony. The scheme uses the mean kinship for each animal to indicate how inter-related it is with the rest of the current breeding colony members. Genome uniqueness is used to provide an indication of whether or not an animal is likely to possess alleles at risk of being lost from the colony. Under the scheme, animals with low mean kinship or high genome uniqueness are ranked more highly.
Breeding Group Formation
One of the goals in breeding group formation is to avoid the potential for mating of closely related animals. Since behavioral concerns and housing constraints will also be taken into account in the group formation process, it is our goal to provide the largest number of animals possible from a list of candidates that can be housed together without risk of consanguineous mating. To that end, this function uses information from the Genetic Value Analysis to search for the largest combinations of animals that can be produced from a list of candidates.
The default options do not consider the sex of individuals when forming the groups, though this has likely been a consideration by the user in selecting the candidate group members. Optionally the user may select to form harem groups, which considers the sex of individuals when forming groups and restricts the number of males to one per group.
For more information see:
A Practical Approach for Designing Breeding Groups to Maximize Genetic
Diversity in a Large Colony of Captive Rhesus Macaques (Macaca
mulatto) Vinson, A ; Raboin, MJ Journal Of The American Association
For Laboratory Animal Science, 2015 Nov, Vol.54(6), pp.700-707 [Peer
Reviewed Journal]