polySegratio-package {polySegratio} | R Documentation |
These functions provide tools for computing expected segregation ratios (or more correctly segregation proportions) for dominant markers in regular autopolyploids and simulating such marker data as well as conducting standard Chi squared tests and Binomial confidance intervals for assigning marker dosage.
Package: | polySegratio |
Type: | Package |
Version: | 0.2-2 |
Date: | 2009-11-18 |
License: | GPL-3 |
Use expected.segRatio
to compute expected segregation
proportions for regular autopolyploids
Use segregationRatios
to compute segregation ratios for
a matrix of markers
Use test.segRatio
to assignmarker dosage via Chi squared
tests or Binomial CIs
Use sim.autoMarkers
and sim.autoCross
to
simulate marker data under various scenarios
Use addMisclass
and addMissing
make some
markers misclassified or missing at random
Peter Baker p.baker1@uq.edu.au
## expected segregation proportions heterogeneous parents expected.segRatio(4) expected.segRatio("Tetraploid") expected.segRatio("Octa") ## expected segregation proportions homogeneous parents expected.segRatio("Octa",type="heter") ## generate dominant markers for autotetraploids a1 <- sim.autoMarkers(4,c(0.8,0.2)) print(a1) plot(a1) ## generate crosses for different parental types p2 <- sim.autoCross(4, dose.proportion=list(p01=c(0.7,0.3), p10=c(0.7,0.3),p11=c(0.6,0.2,0.2))) print(p2) plot(p2) ## simulate and test some markers, printing out a summary table of ## no.s of correct marker dosages a <- sim.autoMarkers(ploidy = 8, c(0.7,0.2,0.09,0.01), type="hetero", n.markers=500,n.individuals=100) a <- addMissing(a, 0.07) # make seven percent missing at random at <- test.segRatio(a$seg.ratios, ploidy=8, type.parents="het", method="bin") print(addmargins(table(a$true.doses$dosage, at$dosage, exclude=NULL)))