Package index • gap

All functions

ACDE(): Fit AE, ACE or ADE biometric mixed models to nuclear family data
AE3(): AE model using nuclear family trios
BFDP(): Bayesian false-discovery probability
ESplot(): Effect-size / Odds-ratio forest plot
FPRP(): False-positive report probability
KCC(): Disease prevalences in cases and controls
LD22(): LD statistics for two diallelic markers
LDkl(): LD statistics for two multiallelic markers
MCMCgrm(): Mixed modeling with genetic relationship matrices
METAL_forestplot(): forest plot as R/meta's forest for METAL outputs
ReadGRM(): A function to read GRM file
ReadGRMBin(): A function to read GRM binary files
snpHWE() PARn() snpPVE() snpPAR(): Functions for single nucleotide polymorphisms
WriteGRM(): A function to write GRM file
WriteGRMBin(): A function to write GRM binary file
a2g(): Allele-to-genotype conversion
ab(): Test/Power calculation for mediating effect
allele.recode(): Allele recoding
asplot(): Regional association plot
b2r(): Obtain correlation coefficients and their variance-covariances
bt(): Bradley-Terry model for contingency table
ccsize(): Power and sample size for case-cohort design
chow.test(): Chow's test for heterogeneity in two regressions
chr_pos_a1_a2(): SNP id by chr:pos+a1/a2
ci2ms(): Effect size and standard error from confidence interval
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
circos.mhtplot2(): Another circos Manhattan plot
cis.vs.trans.classification(): A cis/trans classifier
cnvplot(): genomewide plot of CNVs
comp.score(): score statistics for testing genetic linkage of quantitative trait
cs(): Credible set from summary statistics
fbsize(): Sample size for family-based linkage and association design
g2a(): Conversion of a genotype identifier to alleles
gc.em(): Gene counting for haplotype analysis
gc.lambda(): Estimation of the genomic control inflation statistic (lambda)
gcontrol(): genomic control
gcontrol2(): genomic control based on p values
gcp(): Permutation tests using GENECOUNTING
genecounting(): Gene counting for haplotype analysis
geno.recode(): Genotype recoding
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
gif(): Kinship coefficient and genetic index of familiality
grid2d(): Two-dimensional grid
h2.jags(): Heritability estimation based on genomic relationship matrix using JAGS
h2G(): Heritability and its variance
h2GE(): Heritability and its variance when there is an environment component
h2_mzdz(): Heritability estimation according to twin correlations
h2l(): Heritability under the liability threshold model
hap(): Haplotype reconstruction
hap.control(): Control for haplotype reconstruction
hap.em(): Gene counting for haplotype analysis
hap.score(): Score statistics for association of traits with haplotypes
hg18: Chromosomal lengths for build 36
hg19: Chromosomal lengths for build 37
hg38: Chromosomal lengths for build 38
hmht.control(): Controls for highlighted regions in mhtplot
htr(): Haplotype trend regression
hwe(): Hardy-Weinberg Equilibrium Test (Multiallelic, Unified Interface)
hwe.cc(): A likelihood ratio test of population Hardy-Weinberg equilibrium for case-control studies
hwe.hardy(): Hardy-Weinberg equilibrium test using MCMC
hwe.jags(): Hardy-Weinberg equlibrium test for a multiallelic marker using JAGS
inv_chr_pos_a1_a2(): Retrieval of chr:pos+a1/a2 according to SNP id
invnormal(): Inverse normal transformation
ixy(): Conversion of chrosome name from strings
kin.morgan(): kinship matrix for simple pedigree
klem(): Haplotype frequency estimation based on a genotype table of two multiallelic markers
labelManhattan(): Annotate Manhattan or Miami Plot
log10p(): log10(p) for a normal deviate z
log10pvalue(): log10(p) for a P value including its scientific format
logp(): log(p) for a normal deviate z
makeped(): A function to prepare pedigrees in post-MAKEPED format
masize(): Sample size calculation for mediation analysis
metap(): Meta-analysis of p-values with heterogeneity and random effects
metareg(): Fixed and random effects meta-analysis (vectorised implementation)
mht.control(): Controls for Manhattan plot
mhtplot(): Manhattan plot
mhtplot.trunc(): Truncated Manhattan plot
mhtplot2(): Manhattan plot with annotations
mia(): Multiple imputation analysis for hap
miamiplot(): Miami plot
miamiplot2(): Miami Plot
mr(): Mendelian Randomization wrapper (IVW, Egger, Weighted Median, Penalised WM)
mr_forestplot(): Mendelian Randomization forest plot
mtdt(): Transmission/disequilibrium test of a multiallelic marker
mtdt2(): Transmission/disequilibrium test of a multiallelic marker by Bradley-Terry model
muvar(): Means and variances under 1- and 2- locus (biallelic) QTL model
mvmeta(): Multivariate fixed-effects meta-analysis via generalized least squares
pbsize(): Power for population-based association design
pbsize2(): Power for case-control association design
pedtodot(): Converting pedigree(s) to dot file(s)
pedtodot_verbatim(): Pedigree-drawing with graphviz
pfc(): Probability of familial clustering of disease
pfc.sim(): Probability of familial clustering of disease
pgc(): Preparing weight for GENECOUNTING
plot(<hap.score>): Plot haplotype frequencies versus haplotype score statistics
print(<hap.score>): Print a hap.score object
pvalue(): P value for a normal deviate
qqfun(): Quantile-comparison plots
qqunif(): Q-Q plot for uniformly distributed random variables
qtl2dplot(): 2D QTL plot
qtl2dplotly(): 2D QTL plotly
qtl3dplotly(): 3D QTL plot
qtlClassifier(): A QTL cis/trans classifier
qtlFinder(): Distance-based signal identification
read.ms.output(): A utility function to read ms output
revStrand(): Allele on the reverse strand
runshinygap(): Start shinygap
s2k(): Statistics for 2 by K table
sentinels(): Sentinel identification from GWAS summary statistics
snptest_sample(): A utility to generate SNPTEST sample file
tscc(): Power calculation for two-stage case-control design
whscore(): Whittemore-Halpern scores for allele-sharing
xy(): Conversion of chromosome names to strings