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QTL Hotspots

QTL hotspots, groups of traits co-mapping to the same genomic location, are a common feature of genetical genomics studies. Genomic locations associated with many traits are biologically interesting since they may harbor influential regulators. Nonetheless, non-genetic mechanisms, uncontrolled environmental factors and unmeasured variables are capable of inducing a strong correlation structure among clusters of transcripts, and as a consequence, whenever a transcript shows a spurious linkage, many correlated transcripts will likely map to the same locus, creating a spurious QTL hotspot. Permutation approaches that do not take into account the phenotypic correlation tend to underestimate the size of the hotspots that might appear by change in these situations (Breitling et al. 2008).

This issue motivated the development of permutation tests that preserve the correlation structure of the phenotypes in order to determine the significance of QTL hotspots (Breitling et al. 2008, Chaibub Neto et al. 2012). In this tutorial we present software tools implementing the NL-method (Chaibub Neto et al. 2012), the N-method (Breitling et al. 2008), and the Q-method (West et al. 2007, Wu et al. 2008) permutation approaches.

Installation

devtools::install_github("byandell/qtlhot", build_vignettes=TRUE)

Issues

Modify to use names element of highlod object? Fix so call with length(pheno2) == 1 and > 1 give same results; see JoinTestOutputs.

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Install

install.packages('qtlhot')

Monthly Downloads

79

Version

1.2.10

License

GPL (>= 2)

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Maintainer

Brian Yandell

Last Published

January 19th, 2026

Functions in qtlhot (1.2.10)

ww.perm

Conduct West-Wu (Q) permutation tests
hotperm1

Hotspot Permutation Sample
parallel.qtlhot

Code for parallelizing R/qtlhot.
neqtl

neqtl.R Ported from http://github.com/kbroman/neqtl
SimCrossCausal

Simulate Cross for Causal Tests
include.hotspots

Generate hotspots for the simulated examples in the manuscript.
PrecTpFpMatrix

Compute Precision, True Positives, and False Positives
CMSTCross

MST Sample Cross object
GetCommonQtls

Get common QTLs for phenotypes
CMSTtests

Perform CMST Tests on cross object
highlod

Pull high LOD values with chr and pos.
hotperm

Conduct NL and N permutation tests
hotsize

Hotspot size routines.
GetCandReg

Get genetic information on candidate regulators and co-mapping traits.
filter.threshold

Summary of threshold results
add.phenos

Add phenotypes to cross object.
FitAllTests

Determine false positive and true positive rates for known targets.
quantile_highlod

Compute Quantiles of High LOD Scores
sim.null.cross

Generates a "null dataset" cross
sim.hotspot

Wrapper routine for simulations.
quantile_hotperm

Compute Quantiles for Hotperm Results