qtl-internal {qtl} | R Documentation |
Internal qtl functions. These are generally not to be called by the user.
adjust.rf.ri(r, type=c("self","sib"), chrtype=c("A","X"), expand=TRUE) asnumericwithdec(x, dec=".") calc.genoprob.special(cross, error.prob=0.0001, map.function=c("haldane","kosambi","c-f","morgan")) calc.pairprob(cross, step=0, off.end=0, error.prob=0.0001, map.function=c("haldane","kosambi","c-f","morgan"), map, assumeCondIndep=FALSE) calc.plod(lod, nterms, type=c("f2","bc"), penalties) calcPermPval(peaks, perms) charround(x, digits=1) checkPhyloCrosses(crosses, taxa, nostop=FALSE) checkPhyloPartition(partition, taxa) checkcovar(cross, pheno.col, addcovar, intcovar, perm.strata, ind.noqtl=NULL, verbose=TRUE) checkformula(formula, qtl.name, covar.name) checkStepwiseqtlStart(qtl, formula, covar=NULL) clean(object, ...) condense(object) convert(object, ...) convertMWril(cross, parents, error.prob=0) countqtlterms(formula, ignore.covar=TRUE) create.map(map, step, off.end, stepwidth=c("fixed", "variable", "max")) deparseQTLformula(formula, reorderterms=FALSE) discan(cross, pheno, method=c("em","hk","mr"), addcovar=NULL, intcovar=NULL, maxit=4000, tol=1e-4, verbose=FALSE, give.warnings=TRUE, ind.noqtl) dropfromqtlformula(formula, qtlnum) dropXcol(type=c("f2","bc", "riself", "risib", "4way", "dh", "special"), sexpgm, cross.attr) effectplot.getmark(cross, mname) effectplot.calmeanse(pheno, mark1, mark2, geno1, geno2, ndraws, var.flag=c("pooled", "group")) expandf2covar(thecovar) find.pseudomarkerpos(cross, marker, where=c("draws", "prob")) fitqtlengine(pheno, qtl, covar=NULL, formula, method=c("imp", "hk"), model=c("normal", "binary"), dropone=TRUE, get.ests=FALSE, run.checks=TRUE, cross.attr, sexpgm, tol, maxit) fitstahl.estp(cross, error.prob=0.0001, m=0, tol=1e-4, maxit=4000) fitstahl.estp.sub(p, cross, error.prob=0.0001, m=0, thetol=1e-4, maxit=4000) fitstahl.este(cross, m=0, p=0, tol=1e-4, maxit=4000) fitstahl.este.sub(error.prob, cross, m=0, p=0, thetol=1e-4, maxit=4000) fitstahl.estpe(cross, m=0, tol=1e-4, maxit=4000) fitstahl.estpe.sub(x, cross, m=0, thetol=1e-4, maxit=4000) fixX4write(geno,sex,pgm,crosstype) fixXgeno.bc(cross) fixXgeno.f2(cross, alleles) flipcross(cross) markerforwsel(x, y, maxsize=7) markerforwself2(x, y, maxsize=7) genAllPartitions(n.taxa, taxa) genotab.em(dat, tol=1e-6, maxit=10000, verbose=FALSE) getsex(cross) addmarkerstointervalmap(cross,intervalresult,verbose=FALSE) calculatedensity(cross,distance=30) checkdistances(cross,cofactors,dist=5) circlelocations(nt) drawcirculargenome(result,lodmarkers=FALSE,spacing=50) drawspline(cn1, cn2, lwd = 1,col="blue",...) estimatemarkerlod(interresults) getChr(x) getchromosomelength(result, chr) getgenomelength(result) locationtocircle(result, chr, loc, spacing=50, fixoutofbounds=TRUE, verbose=FALSE) loopthroughmulti(cross,result,save=FALSE,spacing=100) mqmextractpseudomarkers(mqmresult) mqm_version() scanall(cross, scanfunction=scanone, multicore=TRUE, n.clusters=1, batchsize=10, FF=0,cofactors=NULL, ..., plot=FALSE, verbose=FALSE) scoremissingmarkers(cross) stepsize(mqmpseudomarkers) getgenonames(type=c("f2","bc","riself","risib","4way","dh","special"), chrtype=c("A","X"), expandX=c("simple","standard","full"), sexpgm, cross.attr) getThird(x) grab.arg.names(...) imf.cf(r) imf.h(r) imf.k(r) imf.m(r) imf.stahl(r, m=0, p=0, tol=1e-12, maxit=1000) interpmap(oldmap, newmap) interpmap4scantwo(output, newmap) LikePheVector(pheno, n.ind, n.phe) locatemarker(map, pos, chr, flag) makeSSmap(cross) markerloglik(cross, marker, error.prob=0.0001) matchchr(selection, thechr) ## S3 method for class 'scantwocondensed' max(object, lodcolumn=1, what=c("best", "full", "add", "int"), df=FALSE, na.rm=TRUE, ...) mf.cf(d) mf.h(d) mf.k(d) mf.m(d) mf.stahl(d, m=0, p=0) mybinaryrep(n) orderMarkers.sub(cross, chr, window=7, use.ripple=TRUE, verbose=FALSE) ourline() ourstop(...) parseformula(formula, qtl.dimname, covar.dimname) ## S3 method for class 'effectscan' plot(x, gap=25, ylim, mtick=c("line","triangle"), add.legend=TRUE, alternate.chrid=FALSE, ...) polyplot(x, type='b', legend=TRUE,legendloc=0, labels=NULL, cex = par("cex"), pch = 19, gpch = 21, bg = par("bg"), color = par("fg"), col=NULL, ylim=range(x[is.finite(x)]), xlim = NULL, main = NULL, xlab = NULL, ylab = NULL, add=FALSE, ...) ## S3 method for class 'addcovarint' print(x, ...) ## S3 method for class 'addint' print(x, ...) ## S3 method for class 'compactqtl' print(x, ...) ## S3 method for class 'cross' print(x, ...) ## S3 method for class 'map' print(x, ...) ## S3 method for class 'qtl' print(x, ...) ## S3 method for class 'scanoneboot' print(x, ...) ## S3 method for class 'scantwo' print(x, ...) ## S3 method for class 'summary.addpair' print(x, ...) ## S3 method for class 'summary.compactqtl' print(x, ...) ## S3 method for class 'summary.cross' print(x, ...) ## S3 method for class 'summary.fitqtl' print(x, ...) ## S3 method for class 'summary.map' print(x, ...) ## S3 method for class 'summary.qtl' print(x, ...) ## S3 method for class 'summary.ripple' print(x, ...) ## S3 method for class 'summary.scanone' print(x, ...) ## S3 method for class 'summary.scanoneperm' print(x, ...) ## S3 method for class 'summary.scantwo' print(x, ...) ## S3 method for class 'summary.scantwo.old' print(x, ...) ## S3 method for class 'summary.scantwoperm' print(x, ...) printQTLformulanicely(formula, header, width, width2, sep=" ") qtlByPartition(crosses, partition) qtlformulasymmetric(formula, qtlnum1, qtlnum2) read.cro.qtlcart(file) read.cross.csv(dir, file, na.strings=c("-","NA"), genotypes=c("A","H","B","D","C"), estimate.map=TRUE, rotate=FALSE, ...) read.cross.csvs(dir, genfile, phefile, na.strings=c("-","NA"), genotypes=c("A","H","B","D","C"), estimate.map=TRUE, rotate=FALSE, ...) read.cross.gary(dir, genfile, mnamesfile, chridfile, phefile, pnamesfile, mapfile,estimate.map,na.strings) read.cross.karl(dir, genfile, mapfile, phefile) read.cross.mm(dir, rawfile, mapfile, estimate.map=TRUE) read.cross.qtlcart(dir, crofile, mapfile) read.cross.qtx(dir, file, estimate.map=TRUE) read.map.qtlcart(file) read.maps.mm(mapsfile) reorgRIargmax(cross) reorgRIdraws(cross) reorgRIgenoprob(cross) reorgRIpairprob(cross, pairprob) replacemap(object, map) revisecovar(sexpgm, covar) reviseqtlnuminformula(formula, oldnum, newnum) revisescantwodf(df) reviseXdata(type=c("f2","bc"), expandX=c("simple","standard","full"), sexpgm, geno, prob, draws, pairprob, cross.attr, force=FALSE) ripple.perm1(n) ripple.perm2(n) ripple.perm.sub(x, mat) rippleSnowLik(orders, cross, error.prob, map.function, maxit, tol, sex.sp) rippleSnowCountxo(orders, genodat, func) roundqtlpos(x, digits = 1) scanone.perm(cross, pheno.col=1, model=c("normal","binary","2part","np"), method=c("em","imp","hk","ehk","mr","mr-imp","mr-argmax"), addcovar=NULL, intcovar=NULL, weights=NULL, use=c("all.obs", "complete.obs"), upper=FALSE, ties.random=FALSE, start=NULL, maxit=4000, tol=1e-4, n.perm=1000, perm.Xsp=FALSE, perm.strata=NULL, verbose=TRUE, batchsize=250) scanone.perm.engine(n.perm, cross, pheno.col, model, method, addcovar, intcovar, weights, use, upper, ties.random, start, maxit, tol, verbose, perm.strata, batchsize=250) scanoneXnull(type, sexpgm) scantwo.perm(cross, pheno.col=1, model=c("normal","binary"), method=c("em","imp","hk","mr","mr-imp","mr-argmax"), addcovar=NULL, intcovar=NULL, weights=NULL, use=c("all.obs", "complete.obs"), incl.markers=FALSE, clean.output=FALSE, clean.nmar=1, clean.distance=0, maxit=4000, tol=1e-4, verbose=FALSE, n.perm=1000, perm.strata, assumeCondIndep=FALSE, batchsize=250) scantwo.perm.engine(n.perm, cross, pheno.col, model, method, addcovar, intcovar, weights, use, incl.markers, clean.output, clean.nmar=1, clean.distance=0, maxit, tol, verbose, perm.strata, assumeCondIndep=FALSE, batchsize=250) scantwoperm2scanoneperm(scantwoperms) sim.bcg(n.ind, map, m, p, map.function=c("haldane","kosambi","c-f","morgan")) sim.cross.4way(map, model, n.ind, error.prob, missing.prob, partial.missing.prob, keep.errorind, m, p, map.function) sim.cross.bc(map, model, n.ind, error.prob, missing.prob, keep.errorind, m, p, map.function) sim.cross.f2(map, model, n.ind, error.prob, missing.prob, partial.missing.prob, keep.errorind, m, p, map.function) sim.ril(map, n.ril=1, type=c("sibmating", "selfing"), n.str=c("2","4","8"), m=0, p=0, error.prob=0, missing.prob=0, random.cross=TRUE) snowCoreALL(x, all.data, scanfunction, cofactors, verbose=FALSE, ...) snowCoreBOOT(x, all.data, scanfunction, bootmethod, cofactors, verbose=FALSE, ...) sortPhyloPartitions(partitions, taxa) subrousummaryscantwo(object, for.perm=FALSE) ## S3 method for class 'scantwocondensed' summary(object, thresholds, what=c("best", "full", "add", "int"), perms, alphas, lodcolumn=1, pvalues=FALSE, df=FALSE, allpairs=TRUE, ...) ## S3 method for class 'addcovarint' summary(object, ...) ## S3 method for class 'addint' summary(object, ...) ## S3 method for class 'compactqtl' summary(object, ...) testchr(selection, thechr) vbscan(cross, pheno.col=1, upper=FALSE, method="em", maxit=4000, tol=1e-4) write.cross.csv(cross, filestem="data", digits=NULL, rotate=FALSE, split=FALSE) write.cross.gary(cross, digits=NULL) write.cross.mm(cross, filestem="data", digits=NULL) write.cross.qtlcart(cross, filestem="data")
Karl W Broman, kbroman@biostat.wisc.edu