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*A Statistical Toolbox for QTL Analysis*

`BigRiverQTL.jl` is a user-friendly Julia package that supports
efficient and interpretable quantitative trait locus (QTL)
analysis. This comprehensive toolbox encompasses three core components
tailored to streamline the entire QTL analysis workflow:
preprocessing, genomic scanning, and result visualization.
`BigRiverQTL.jl` is a package that makes it easier to perform
quantitative trait locus (QTL) analysis in Julia. It consists of
three components streamline the QTL analysis workflow:
preprocessing, genome scans, and visualization.

- **Preprocessing:** The preprocessing functions are designed to
seamlessly import and convert genomic data into an efficient and
memory-conservative format. This component also offers function
capabilities for quickly calculating kinship matrices, ensuring data
readiness for subsequent analysis phases.

- **Genomic Scanning:** `BigRiverQTL.jl` provides advanced genomic
scanning capabilities through `BulkLMM.jl` for swift single-trait
scans, which surpass other methods in terms of computational
speed. For analyses involving multiple traits, the package employs
`FlxQTL.jl`, a cutting-edge approach that detects complex trait
interrelations.

- **Result Visualization:** The third component of `BigRiverQTL.jl`
enriches the analytical experience by offering plotting tools
designed to illustrate the outcomes of genomic scans. The plotting
functions are useful for interpreting the results and aid in the
derivation of meaningful conclusions

- **Genome Scans:** We provide the capabilities to perform a large
number of univariate genome scans using
[`BulkLMM.jl`](https://github.com/senresearch/BulkLMM.jl). For
analyses involving multiple traits, we provide an interface to
[`FlxQTL.jl`](https://github.com/senresearch/FlxQTL.jl) to analyze
longitudinal traits and complex trait correlations.

- **Visualization:** The third component of the package offers
plotting tools designed to visualize genome scans including eQTL
scans using the
[`BigRiverQTLPlots.jl`](https://github.com/senresearch/BigRiverQTLPlots.jl)
package.

## Installation

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