rrblup_rs/
lib.rs

1//! # rrblup-rs
2//!
3//! Rust implementation of the [R/rrBLUP](https://cran.r-project.org/package=rrBLUP) package
4//! for mixed model analysis and genomic prediction.
5//!
6//! ## Features
7//!
8//! - [`mixed_solve`](mixed_solve::mixed_solve) - REML-based mixed model solver
9//! - [`a_mat()`] - Additive relationship matrix from marker data
10//! - [`kin_blup()`] - Genomic BLUP with kinship matrix
11//!
12//! ## Example
13//!
14//! ```
15//! use rrblup_rs::mixed_solve::{mixed_solve, MixedSolveOptions};
16//!
17//! let y = vec![1.0, 2.0, 3.0, 4.0, 5.0];
18//! let result = mixed_solve(&y, None, None, None, None).unwrap();
19//! println!("Vu = {}, Ve = {}", result.vu, result.ve);
20//! ```
21//!
22//! ## References
23//!
24//! Endelman, J.B. 2011. Ridge regression and other kernels for genomic selection
25//! with R package rrBLUP. Plant Genome 4:250-255.
26
27/// REML-based mixed model solver.
28pub mod mixed_solve;
29
30/// Additive relationship matrix computation from marker data.
31pub mod a_mat;
32
33/// Genomic BLUP with kinship matrix.
34pub mod kin_blup;
35
36// Re-export main types and functions from mixed_solve
37pub use mixed_solve::{
38    mixed_solve as mixed_solve_reml, Method, MixedSolveOptions, MixedSolveResult,
39};
40
41// Re-export main types and functions from a_mat
42pub use a_mat::{a_mat, AMatOptions, AMatResult, ImputeMethod, ShrinkConfig, ShrinkMethod};
43
44// Re-export main types and functions from kin_blup
45pub use kin_blup::{kin_blup, KinBlupData, KinBlupOptions, KinBlupResult};