QTL_R2: QTL global and partial R squared
In vincentgarin/mppR: Multi-Parent Population QTL Analysis

QTL_R2

R Documentation

QTL global and partial R squared

Description

Computes the global and partial (adjusted) R squared of a list of QTLs using a linear model.

Usage

QTL_R2(mppData, trait = 1, QTL = NULL, Q.eff = "cr", glb.only = FALSE)

Arguments

`mppData`	An object of class `mppData`.
`trait`	`Numerical` or `character` indicator to specify which trait of the `mppData` object should be used. Default = 1.
`QTL`	Object of class `QTLlist` representing a list of selected position obtained with the function `QTL_select` or vector of `character` marker positions names. Default = NULL.
`Q.eff`	`Character` expression indicating the assumption concerning the QTL effects: 1) "cr" for cross-specific; 2) "par" for parental; 3) "anc" for ancestral; 4) "biall" for a bi-allelic. For more details see `mpp_SIM`. Default = "cr".
`glb.only`	`Logical` value. If glb.only = TRUE, only the global and global adjusted R squared will be returned. Default = FALSE.

Details

The function computes R squared statistics using a linear model. The extra variance explained by a full model containing the QTL terms with respect to a reduced model containing only the cross intercept terms and uses the ratio between the residual sum of square of these two models: R2 = 1-(RSS(f))/(RSS(r)).

Partial R squared for each individual QTL position can also be calculated. Two types of partial R squared are returned. The first one uses the difference between the R squared obtained with all QTL positions and the R squared obtain with all position minus the ith one (difference R squared). The second method used only the ith QTL position in the model (single R squared).

For both global and partial R squared, it is possible to obtained adjusted measurements taking the number of degrees of freedom into consideration using an adaptation of the formula given by Utz et al. (2000): R.adj = R-(z/(N-z-n.cr))*(1-R) where z is the total number of estimated components of the genetic effect. N is the total number of phenotypic information, and n.cr is the number of intercept (cross) terms.

Value

Return:

object of class QR2Res containing the following objects:

`glb.R2`	Global R squared of all QTL terms.
`glb.adj.R2`	Global adjusted R squared of all QTL terms.
`part.R2.diff`	Vector of partial R squared doing the difference between the full model and a model minus the ith QTL.
`part.adj.R2.diff`	Vector of partial adjusted R squared doing the difference between the full model and a model minus the ith QTL.
`part.R2.sg`	Vector of partial R squared using only the ith QTL.
`part.adj.R2.sg`	Vector of partial adjusted R squared using only the ith QTL.

Author(s)

Vincent Garin

References

Utz, H. F., Melchinger, A. E., & Schon, C. C. (2000). Bias and sampling error of the estimated proportion of genotypic variance explained by quantitative trait loci determined from experimental data in maize using cross validation and validation with independent samples. Genetics, 154(4), 1839-1849.

Examples


data(mppData)

SIM <- mpp_SIM(mppData)
QTL <- QTL_select(Qprof = SIM, threshold = 3, window = 20)
Q_R2 <- QTL_R2(mppData = mppData, QTL = QTL, Q.eff = "cr")
summary(Q_R2)

vincentgarin/mppR documentation built on March 13, 2024, 7:30 p.m.