Initial submission to Bioconductor.
loopQTL maps chromatin loop QTLs from Hi-C: which SNPs at a loop's
anchors associate with the loop's contact strength across samples. The
package tests only SNPs that fall inside a loop's anchor bins rather
than every SNP in a wide cis-window, so signal is concentrated on the
variants biologically relevant to whether that specific loop forms.
The full workflow is documented in the package vignette with below functions included:
loopQTLsetup() -- Validate inputs and build loopQTL object.loopQTLnormalize() -- Cross-normalization on Hi-C signal.loopQTLchooseK() -- Auto-select the number of PCs for covariates.runQTL() -- Anchor-restricted association testing.loopQTLpairData() -- Sample-level view of one loop × SNP pair.loopQTLannotate() -- Annotate loopQTL results with target genes and
regulatory peaks.loopQTLplotPair() -- Per-sample boxplot for a single SNP-loop pair.loopQTLplotLocus() -- Locus-level track view of loops, SNPs, and genes.loopQTLplotSnpWindow() -- Hi-C-style beta heatmap around a SNP.A 10-sample Hi-C test dataset is bundled under inst/extdata/. So the vignette, and the example
function documentation run end-to-end without external downloads.