crosshap
is an LD-based local haplotype analysis and visualization
tool.
Given a genomic variant data for a region of interest, crosshap
performs LD-based local haplotyping. Tightly linked variants are
clustered into Marker Groups (MGs), and individuals are grouped into
local haplotypes by shared allelic combinations of MGs. Following this,
crosshap
provides a range of visualization options to examine relevant
characteristics of the linked Marker Groups and local haplotypes.
crosshap
was originally designed to explore local haplotype patterns
that may underlie phenotypic variability in quantitative trait locus
(QTL) regions. It is ideally suited to complement and follow-up GWAS
results (takes same inputs). crosshap
equips users with the tools to
explain why a region reported a GWAS hit, what variants are causal
candidates, what populations are they present/absent in, and what the
features are of those populations.
Alternatively, crosshap
can simply be a tool to identify patterns of
linkage among local variants, and to classify individuals based on
shared haplotypes.
Note: crosshap
is designed for in-depth, user-driven analysis of
inheritance patterns in specific regions of interest, not genome-wide
scans.
crosshap
is available on CRAN:
install.packages("crosshap")
For the latest features, you can install the development version of
crosshap
from GitHub with:
# install.packages("devtools")
devtools::install_github("JacobIMarsh/crosshap")
In short, a typical crosshap analysis workflow involves the following steps. For a detailed explanation and walk through, see our Getting started vignette.
- Read in raw inputs
read_vcf(region.vcf)
read_LD(plink.ld)
read_metadata(metadata.txt)
read_pheno(pheno.txt)
- Run local haplotyping at a range of epsilon values
HapObject <- run_haplotyping(vcf, LD, metadata, pheno, epsilon, MGmin)
- Build clustering tree to optimize epsilon value
clustree_viz(HapObject)
- Visualize local haplotypes and Marker Groups
crosshap_viz(HapObject, epsilon)
From here you can examine haplotype and Marker Group features from the visualization, and export relevant information from the haplotype object.
HapObject$Haplotypes_MGmin30_E0.6$Indfile
HapObject$Haplotypes_MGmin30_E0.6$Hapfile
HapObject$Haplotypes_MGmin30_E0.6$Varfile
For technical queries feel free to contact me: jacob.marsh@unc.edu . Please contact Prof. David Edwards for all other queries: dave.edwards@uwa.edu.au .