---
title: "Inbred Based Populations"
author: "[Statistical Genetics Lab](http://statgen.esalq.usp.br) <br/> Department of Genetics <br/> Luiz de Queiroz College of Agriculture <br/> University of São Paulo"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Inbred Based Populations}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r knitr_init, echo=FALSE, cache=FALSE, message=FALSE, cache.comments=FALSE, comment=FALSE, warning=FALSE}

knitr::opts_chunk$set(collapse = TRUE,
                      comment = "#>",
                      fig.width = 6,
                      fig.height = 6,
                      fig.align = "center",
                      dev = "png",
                      dpi = 36,
                      cache = TRUE)

```


**[Access the complete version of this vignette here](https://cristianetaniguti.github.io/onemap/Inbred_Based_Populations.html)**

To have access to all example datasets. Install `onemap` from GitHub and run the following command:

```{r, eval=FALSE}
#install.packages("devtools") ## if you do not have it installed
devtools::install_github("cristianetaniguti/onemap")
```


Starting in version 2.0-0, `OneMap` can also deal with inbred-based
populations, that is, populations that have homozygous parental lines in
the genealogy (F2s, backcrosses, and RILs). As a consequence, linkage
phases do not need to be estimated. Since version 2.3.0, phases are estimated 
for F2 populations to properly generate progeny haplotypes not only the 
recombination fraction.

In this vignette, we explain how to proceed with the analysis in an F2
population. The same procedure can be used for backcrosses and RILs as
well, and therefore users should not have any difficulty in analyzing
their data. However, there are a number of differences from genetic
mapping in outcrossing species; please read the proper vignette.

If you are not familiar with `R`, we recommend first the reading of
vignette
[Introduction to R](https://cristianetaniguti.github.io/onemap/Introduction_R.html).
You do not need to be an expert in R to build your linkage map, but
some concepts are necessary and will help you through the process.

The software has been available on CRAN since 2007 
([OneMap on CRAN](https://cran.r-project.org/package=onemap)) and has 
undergone several updates, adding new features and optimization up to version 3.2.0 in 2024. 
Future updates will focus solely on maintaining accessibility and functionality. 
**New feature development and optimization efforts are now being directed toward the 
[MAPpoly](https://github.com/mmollina/MAPpoly) and 
[MAPpoly2](https://github.com/mmollina/mappoly2) packages**.  

**MAPpoly** is a more robust package designed for constructing linkage maps
 in polyploid species. Its optimized algorithms also provide improved efficiency for 
diploid species compared to OneMap. Therefore, we recommend using MAPpoly instead 
of OneMap in the following scenarios for diploid species:  

- When working with only biallelic markers (e.g., SNPs).  
- For outcrossing full-sib (F1), F2, or backcross populations.  
- For datasets with a large number of markers (>5,000).  
- For multi-population datasets (e.g., progeny from multiple parents; see MAPpoly2).  

However, **OneMap** remains the best choice if you have:  

- Populations derived from recombinant inbred lines (RILs).  
- Datasets with multiallelic or dominant markers.  

For guidance on best practices in building linkage maps while accounting for genotyping 
errors, please refer to Taniguti et. al 2023.