Function reference • GUESSFM

All functions
`GUESSFM`	GUESSFM
`abf.calc()`	Calculate Approximate Bayes Factors
`abf.fit.parallel.setup()`	Internal function: create parallel.dir, save necessary files
`abf.speedglm.fit()`	abf.speedglm.fit
`abf2snpmod()`	abf2snpmod
`snps()` `tags()`	Accessors for groups objects
`addlines()`	addlines
`best.models()`	Best models
`best.snps()`	Best SNPs
`calc.maxmin()`	calculate max or min of subset of a matrix
`check.merge()`	Check if snp groups can be combined
`cond.best()`	cond.best
`convert()`	Convert from old definitions of groups, tags classes to new
`cummean()`	internal function: cumulative mean
`ess.read()`	ess.read
`ess2snpmod()`	ess2snpmod
`expand.tags()`	Expand tags for a snpmod object
`ggbed()`	Plot a bed file
`ggchr()`	ggchr
`ggld()`	ggld
`ggsnp()`	ggsnp
`group.multi()`	Group SNPs
`groups-class`	Group focused class for holding information about sets of SNPs defined by their mutual LD
`tagsof()` `taggedby()` `[`(<groups>,<character>,<missing>,<missing>) `[`(<groups>,<numeric>,<missing>,<missing>) `[`(<groups>,<logical>,<missing>,<missing>) `[`(<tags>,<character>,<missing>,<missing>) `[[`(<groups>,<numeric>) `[[`(<groups>,<logical>) `[[`(<groups>,<character>)	`tagsof` shows tags for a named character vector of SNPs
`groups.merge()`	merge groups
`guess.read()`	guess.read
`guess.summ()`	Summarise a snpmod object
`impute.missing()`	Fill in missing values in SnpMatrix object
`makestr()`	Paste a list of SNPs in a consistent way to create a model name
`model.union()`	Model unions
`nmodes()`	nmodes
`overlap()`	overlap
`pattern.plot()`	pattern.plot
`plot(<snppicker>,<missing>)` `plot(<ppnsnp>,<missing>)`	Plots
`plot_diffuse()`	Diffusion plot
`plotsummary()`	Summary plots
`pp.nsnp()`	Summarize the posterior model support by the number of SNPs contained in a model
`ppnsnp-class`	Class to hold results of pp.nsnp
`qc()`	Quality control
`read.decode()`	read.decode
`read.ess()`	ess.read
`read.snpmod()`	read.snpmod
`run.bvs()`	Bayesian variable selection
`scalepos()`	Scale SNP positions
`show(<snpmod>)` `show(<snppicker>)` `show(<ppnsnp>)` `show(<tags>)` `show(<groups>)`	Show
`show.ld()`	show.ld
`signal.plot()`	Signal Plot
`skewness()`	skewness
`snp.picker()`	snp.picker
`snpin()`	Check whether a snp is in a snppicker, groups or tags object
`snpmatrix.combine()`	snpmatrix.combine
`snpmod-class`	Class to hold data relating to multiple models fitted to SNP data
`snpmod.add()`	snpmod.add
`snppicker-class`	Class to hold results of snp.picker algorithm
`[`(<snppicker>,<ANY>,<missing>,<missing>) `[[`(<snppicker>,<ANY>)	Subset snppicker object
`snpprior()`	snpprior
`snps.from.correlated.models()`	snps.from.correlated.models
`summ.setminmax()`	summ.setminmax
`summary(<snppicker>)` `summary(<groups>)`	Summaries
`tag()`	tag
`textvenn()`	textvenn
`union()`	Create a union of groups, snppicker or tags objects
`xscale()`	xscale

Reference

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