scaCompute: SCA computation

In GOVS-pack/GOVS: Genome optimization via virtual simulation

SCA computation

Description

Calculate hybrid special combining ability (SCA) based F1 phenotypic values.

Usage

scaCompute(phe_df,which_male,which_female,trait,seqname)

Arguments

phe_df	Phenotypic data frame, row represents F1 combination and includes the paternal information in columns.
which_male	The column index of paternal IDs.
which_female	The column index of maternal IDs.
trait	A character string to define which trait GCA will be computed, this function support two or more phenotypic GCA be computed at the same time.
seqname	A character array regarding hybrid IDs

Value

A data frame involves of target trait SCA.

Author(s)

Qian Cheng, Shuqin Jiang, Xiangfeng Wang

See Also

gcaCompute

Examples

## simulation data
df <- data.frame(seqname = paste0("sample",1:500),
                 female_ID = sample(paste0("female",1:20), size = 500, replace = TRUE),
                 male_ID = sample(paste0("male",1:10), size = 500, replace = TRUE),
                 trait = rnorm(500, mean = 225, sd = 20))
plot(density(df$trait))

## compute SCA of hybrid lines
scaRes <- scaCompute(df,which_female = "female_ID",which_male = "male_ID",
                     trait = "trait",seqname = df$seqname)

GOVS-pack/GOVS documentation built on Oct. 9, 2022, 8:29 a.m.