abbababa.xyioStats: abbababa.xyioStats

In kullrich/distIUPAC: calculates IUPAC distances on Biostrings DNAStringSet and BStringSet objects

Description

This function calculates ABBA-BABA statistics comparing two populations (x: receiver; y: donor) with an ingroup population (i: ingroup) and an outgroup population (o: outgroup). In a four-taxon scenario (((P1,P2),P3),O) with geneflow from P3>>P2, the populations should be defined as follows [x:P2 y:P3 i:P1 o:P4]. Accordingly in the four-taxon scenario (((P1,P2),P3),O) with geneflow from P2>>P3, the populations should be defined as follows [x:P3 y:P2 i:P1 o:P4].

Usage

abbababa.xyioStats(tmpSEQ, x.pos, y.pos, i.pos, o.pos, x.freq = 1,
  y.freq = 1, i.freq = 1, o.freq = 1, x.name = "x", y.name = "y",
  i.name = "i", o.name = "o")

Arguments

tmpSEQ	DNAStringSet [mandatory]
x.pos	population X positions [mandatory]
y.pos	population Y positions [mandatory]
i.pos	population I positions [mandatory]
o.pos	population O positions [mandatory]
x.freq	minimal frequency for population X to keep site [default: 1.0]
y.freq	minimal frequency for population Y to keep site [default: 1.0]
i.freq	minimal frequency for population I to keep site [default: 1.0]
o.freq	minimal frequency for population O to keep site [default: 1.0]
x.name	population X name [default: "x"]
y.name	population Y name [default: "y"]
i.name	population I name [default: "i"]
o.name	population O name [default: "o"]

Author(s)

Kristian K Ullrich

References

Reich, D., Thangaraj, K., Patterson, N., Price, A. L., & Singh, L. (2009). Reconstructing Indian population history. Nature, 461(7263), 489.

Patterson, N., Moorjani, P., Luo, Y., Mallick, S., Rohland, N., Zhan, Y., ... & Reich, D. (2012). Ancient admixture in human history. Genetics, 192(3), 1065-1093.

Martin, S. H., Davey, J. W., & Jiggins, C. D. (2014). Evaluating the use of ABBA–BABA statistics to locate introgressed loci. Molecular biology and evolution, 32(1), 244-257.

See Also

xyioStats, diploid2haploid

Examples

##Use the 'xyioStats' function to handle population assignment automatically

##load sequence data
data("MySequences", package="distIUPAC")
CAS.pos<-5:34
AFG.pos<-82:87
IRA.pos<-71:78
APO.pos<-1

##Here, one needs to consider the changed x, y and i positions due
##to sub-sampling.
CAS.pos_<-seq_along(CAS.pos)
AFG.pos_<-seq(from=length(CAS.pos_)+1, to=length(c(CAS.pos, AFG.pos)))
IRA.pos_<-seq(from=length(c(CAS.pos, AFG.pos))+1,
to=length(c(CAS.pos, AFG.pos, IRA.pos)))
APO.pos_<-seq(from=length(c(CAS.pos, AFG.pos, IRA.pos))+1,
to=length(c(CAS.pos, AFG.pos, IRA.pos, APO.pos)))

##pairwise deletion
CAS_AFG_IRA_APO.pairwiseDeletion.dist<-distIUPAC(
  as.character(MySequences[c(CAS.pos,AFG.pos,IRA.pos,APO.pos)]))
CAS_AFG_IRA_APO.pairwiseDeletion.xyioStats<-dist.xyioStats(
  CAS_AFG_IRA_APO.pairwiseDeletion.dist, 
  x.pos=CAS.pos_, y.pos=AFG.pos_, i.pos=IRA.pos_, o.pos=APO.pos_,
  x.name="CAS", y.name="AFG", i.name="IRA", o.name="APO")

##global deletion
CAS_AFG_IRA_APO.globalDeletion.dist<-distIUPAC(
  as.character(globalDeletion(MySequences[c(CAS.pos,AFG.pos,
  IRA.pos,APO.pos)])))
CAS_AFG_IRA_APO.globalDeletion.xyioStats<-dist.xyioStats(
  CAS_AFG_IRA_APO.globalDeletion.dist,
  x.pos=CAS.pos_, y.pos=AFG.pos_, i.pos=IRA.pos_, o.pos=APO.pos_,
  x.name="CAS", y.name="AFG", i.name="IRA", o.name="APO")

##compare results
rbind(CAS_AFG_IRA_APO.pairwiseDeletion.xyiStats,
  CAS_AFG_IRA_APO.globalDeletion.xyiStats)

kullrich/distIUPAC documentation built on Jan. 9, 2020, 2:50 p.m.