xyioStats: xyioStats

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

Description

This function calculates distIUPAC based distances comparing two populations (x: receiver and y: donor) with an ingroup population (i: ingroup) and an outgroup population (o: outgroup). In the four-taxon scenario (((P1,P2),P3),O) with geneflow from P3>>P2, the populations should be defined for deltaMean and deltaMin statistics 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 for RND, Gmin and RNDmin statistics as follows [x:P3 y:P2 i:P1 o:P4]. Optional, ABBA-BABA statisctis can be calculated concordantly on the four-taxon scenario (((P1:i,P2:x),P3:y),O:o).

Usage

xyioStats(dna, x.pos, y.pos, i.pos, o.pos, x.name = "x", y.name = "y",
  i.name = "i", o.name = "o", chr.name = "chr", wlen = 25000,
  wjump = 25000, start.by = 1, end.by = NULL, wtype = "bp",
  dist = "IUPAC", global.deletion = TRUE, threads = 1, ncores = 1,
  pB = FALSE, do.ABBA = FALSE, x.freq = 1, y.freq = 1,
  i.freq = 1, o.freq = 1)

Arguments

dna	DNAStringSet [mandatory]
x.pos	population X positions [P2 population in the four-taxon scenario (((P1,P2),P3),O) with geneflow from P3>>P2] [mandatory]
y.pos	population Y positions [P3 population in the four-taxon scenario (((P1,P2),P3),O) with geneflow from P3>>P2] [mandatory]
i.pos	population I positions [P1 population in the four-taxon scenario (((P1,P2),P3),O) with geneflow from P3>>P2] [mandatory]
o.pos	population I positions [P4 population in the four-taxon scenario (((P1,P2),P3),O) with geneflow from P3>>P2] [mandatory]
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"]
chr.name	chromosome name [default: "chr"]
wlen	sliding windows length [default: 25000]
wjump	sliding windows jump [default: 25000]
start.by	optional start position [default: 1]
end.by	optional end position [default: NULL]
wtype	sliding windows type to use bp, biSites or triSites [default: "bp"]
dist	distance to use, choose one model as in dist.dna or [default: "IUPAC"]
global.deletion	a logical indicating whether to delete the sites with missing data in a global or pairwise way (default is to delete in a global way) [default: TRUE]
threads	number of parallel threads [default: 1]
ncores	number of parallel cores to process pairwise distance calculation [default: 1]
pB	specifies if progress should be shown as a progress bar [default: FALSE]
do.ABBA	specifies if ABBA-BABA statistics should be calculated [default: FALSE]
x.freq	[default: 1.0]
y.freq	[default: 1.0]
i.freq	[default: 1.0]
o.freq	[default: 1.0]

Author(s)

Kristian K Ullrich

References

Slatkin, M. (1991). Inbreeding coefficients and coalescence times. Genetics Research, 58(2), 167-175.

Beerli, P. (1998). Structured Populations. Advances in molecular ecology, 306, 39.

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.

Peter, B. M. (2016). Admixture, population structure, and F-statistics. Genetics, 202(4), 1485-1501.

Rosenzweig, B. K., Pease, J. B., Besansky, N. J., & Hahn, M. W. (2016). Powerful methods for detecting introgressed regions from population genomic data. Molecular ecology, 25(11), 2387-2397.

Paradis, E., & Schliep, K. (2018). ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics, 35(3), 526-528.

Hahn, M. W., Hibbins, M. S. (2019). A Three-Sample Test for Introgression. Molecular biology and evolution, msz178.

See Also

dist.xyioStats, dist.dna

Examples

data("MySequences", package="distIUPAC")
CAS.pos<-5:34
AFG.pos<-82:87
SPRE.pos<-106:113
APO.pos<-1
AFG.SPRE.CAS.APO.xyioStats<-xyioStats(MySequences, x.pos=AFG.pos,
y.pos=SPRE.pos, i.pos=CAS.pos, o.pos=APO.pos,
x.name="AFG", y.name="SPRE", i.name="CAS", o.name="APO",
threads=2)
AFG.SPRE.CAS.APO.xyioStats

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