gap-package {gap}R Documentation

Genetic analysis package

Description

As first reported [Zhao, J. H. 2007. "gap: Genetic Analysis Package". JSS 23(8):1-18. doi: 10.18637/jss.v023.i08], it is designed as an integrated package for genetic data analysis of both population and family data. Currently, it contains functions for sample size calculations of both population-based and family-based designs, probability of familial disease aggregation, kinship calculation, statistics in linkage analysis, and association analysis involving genetic markers including haplotype analysis with or without environmental covariates. Over years, the package has been developed in-between many projects hence also in line with the name (gap).

Details

Package: gap
Version: 1.2.3-6
Depends: R(>= 2.1.0)
Imports: dplyr, ggplot2, plotly
Suggests: BradleyTerry2, MASS, Matrix, MCMCglmm, R2jags, bdsmatrix,
calibrate, circlize, coda, cowplot, coxme, dplyr, foreign, forestplot,
gap.datasets, ggplot2, grid, haplo.stats, htmlwidgets, kinship2, lattice,
magic, matrixStats, meta, metafor, mets, nlme, pedigree, pedigreemm,
plotrix, qqman, regress, reshape, rmarkdown, rmeta, rms, survival
License: GPL (>=2)
URL: https://jinghuazhao.github.io/R

Index:

ANALYSIS
AE3 AE model using nuclear family trios
bt Bradley-Terry model for contingency table
ccsize Power and sample size for case-cohort design
cs Credibel set
fbsize Sample size for family-based linkage and association design
gc.em Gene counting for haplotype analysis
gcontrol genomic control
gcontrol2 genomic control based on p values
gcp Permutation tests using GENECOUNTING
gc.lambda Estimation of the genomic control inflation statistic (lambda)
genecounting Gene counting for haplotype analysis
gif Kinship coefficient and genetic index of familiality
gsmr Mendelian randomization analysis
hap Haplotype reconstruction
hap.em Gene counting for haplotype analysis
hap.score Score statistics for association of traits with haplotypes
htr Haplotype trend regression
h2.jags Heritability estimation based on genomic relationship matrix using JAGS
hwe Hardy-Weinberg equilibrium test for a multiallelic marker
hwe.cc A likelihood ratio test of population Hardy-Weinberg equilibrium
hwe.hardy Hardy-Weinberg equilibrium test using MCMC
hwe.jags Hardy-Weinberg equlibrium test for a multiallelic marker using JAGS
invnormal inverse Normal transformation
kin.morgan kinship matrix for simple pedigree
LD22 LD statistics for two diallelic markers
LDkl LD statistics for two multiallelic markers
lambda1000 A standardized estimate of the genomic inflation scaling to
a study of 1,000 cases and 1,000 controls
log10p log10(p) for a standard normal deviate
log10pvalue log10(p) for a P value including its scientific format
logp log(p) for a normal deviate
masize Sample size calculation for mediation analysis
MCMCgrm Mixed modeling with genetic relationship matrices
mia multiple imputation analysis for hap
mtdt Transmission/disequilibrium test of a multiallelic marker
mtdt2 Transmission/disequilibrium test of a multiallelic marker
by Bradley-Terry model
mvmeta Multivariate meta-analysis based on generalized least squares
pbsize Power for population-based association design
pbsize2 Power for case-control association design
pfc Probability of familial clustering of disease
pfc.sim Probability of familial clustering of disease
pgc Preparing weight for GENECOUNTING
print.hap.score Print a hap.score object
s2k Statistics for 2 by K table
sentinels Sentinel identification from GWAS summary statistics
tscc Power calculation for two-stage case-control design
GRAPHICS
asplot Regional association plot
ESplot Effect-size plot
circos.cis.vs.trans.plot circos plot of cis/trans classification
circos.cnvplot circos plot of CNVs
circos.mhtplot circos Manhattan plot with gene annotation
cnvplot genomewide plot of CNVs
makeRLEplot make relative log expression plot
METAL_forestplot forest plot as R/meta's forest for METAL outputs
mhtplot Manhattan plot
mhtplot2 Manhattan plot with annotations
pqtl2dplot 2D pQTL plot
pqtl2dplotly 2D pQTL plotly
pqtl3dplotly 3D pQTL plotly
mhtplot.trunc truncated Manhattan plot
miamiplot Miami plot
pedtodot Converting pedigree(s) to dot file(s)
plot.hap.score Plot haplotype frequencies versus haplotype score statistics
qqfun Quantile-comparison plots
qqunif Q-Q plot for uniformly distributed random variable
UTITLITIES
SNP Functions for single nucleotide polymorphisms (SNPs)
BFDP Bayesian false-discovery probability
FPRP False-positive report probability
ab Test/Power calculation for mediating effect
b2r Obtain correlation coefficients and their variance-covariances
chow.test Chow's test for heterogeneity in two regressions
chr_pos_a1_a2 Form SNPID from chromosome, posistion and alleles
cis.vs.trans.classification a cis/trans classifier
comp.score score statistics for testing genetic linkage of quantitative trait
GRM functions ReadGRM, ReadGRMBin, ReadGRMPLINK, ReadGRMPCA, WriteGRM,
WriteGRMBin, WriteGRMSAS
handle genomic relationship matrix involving other software
get_b_se Get b and se from AF, n, and z
get_pve_se Get pve and its standard error from n, z
get_sdy Get sd(y) from AF, n, b, se
h2G A utility function for heritability
h2GE A utility function for heritability involving gene-environment interaction
h2l A utility function for converting observed heritability to its counterpart
under liability threshold model
h2_mzdz Heritability estimation according to twin correlations
klem Haplotype frequency estimation based on a genotype table
of two multiallelic markers
makeped A function to prepare pedigrees in post-MAKEPED format
metap Meta-analysis of p values
metareg Fixed and random effects model for meta-analysis
muvar Means and variances under 1- and 2- locus (diallelic) QTL model
read.ms.output A utility function to read ms output
revStrand Allele on the reverse strand
runshinygap Start shinygap
snptest_sample A utility to generate SNPTEST sample file
whscore Whittemore-Halpern scores for allele-sharing
weighted.median Weighted median with interpolation

We have incorporated functions for a wide range of problems. Nevertheless, this largely remains as a preliminary work to be consolidated in the near future.

Author(s)

Jing Hua Zhao in collaboration with other colleagues, and with help from Kurt Hornik and Brian Ripley of the R core development team

maitained by Jing Hua Zhao <jinghuazhao@hotmail.com>

References

Zhao JH, gap: genetic analysis package. Journal of Statistical Software 2007, 23(8):1-18, doi: 10.18637/jss.v023.i08.

See Also

Useful links:


[Package gap version 1.2.3-6 Index]