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Implementation of QTL Analysis Using r-qtl2 in GeneNetwork
Tags
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Assigned: alexm
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Keywords: RQTL, GeneNetwork2, implementation
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Type: Feature
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Status: In Progress
Description
This document outlines the implementation of a QTL analysis tool in GeneNetwork using r-qtl2 (see docs: https://kbroman.org/qtl2/) and explains what the script does. This PR contains the implementation of the r-qtl2 script for genenetwork:
Tasks
The script currently aims to achieve the following:
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[x] Parsing arguments required for the script
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[x] Data validation for the script
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[x] Generating the cross file
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[x] Reading the cross file
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[x] Calculating genotype probabilities
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[x] Performing Geno Scan (scan1) using HK, LOCO, etc.
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[x] Finding LOD peaks
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[x] Performing permutation tests
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[x] Conducting QTL analysis for multiparent populations
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[ ] Generating required plots
How to Run the Script
The script requires an input file containing all the necessary data to generate the control file. Example:
{
"crosstype": "riself",
"geno_file": "grav2_geno.csv",
"geno_map_file": "grav2_gmap.csv",
"pheno_file": "grav2_pheno.csv",
"phenocovar_file": "grav2_phenocovar.csv"
}
In addition other parameters required are
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output file (A file path of where the output for the script will be generated)
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--directory ( A workspace of where to generate the control file)
Optional parameters include
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--output_file: The file path where the output for the script will be generated.
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--directory: The workspace directory where the control file will be generated.
Optional parameters:
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--cores: The number of cores to use (set to 0 for using all cores).
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--method: The scanning method to use (e.g., Haley-Knott, Linear Mixed Model, or LMM with Leave-One-Chromosome-Out).
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--pstrata: Use permutation strata.
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--threshold: Minimum LOD score for a peak.
An example of how to run the script:
Rscript rqtl2_wrapper.R --input_file [file_path] --directory [workspace_dir] --output_file [file_path] --nperm 100 --cores 3
Related issues:
https://issues.genenetwork.org/topics/lmms/rqtl2/using-rqtl2