A SNP matrix of admixted individuals with SNPs in the rows, samples in the
columns. The elements of the matrix are the genotypes being coded as
the number of copies of the variant allele present, 0, 1 or 2.
position
A vector for the physical postions of the SNPs
anc1
A SNP matrix of ancestry 1 samples with SNPs in the
rows, samples in the columns. The elements of the matrix are the
genotypes being coded as the number of copies of the variant
allele present, 0, 1 or 2.
anc2
A SNP matrix of ancestry 2 samples with SNPs in the
rows, samples in the columns. The elements of the matrix are the
genotypes being coded as the number of copies of the variant
allele present, 0, 1 or 2.
anc3
An optional SNP matrix of ancestry 3 samples with SNPs in the
rows, samples in the columns (default NULL). The elements of the matrix are the
genotypes being coded as the number of copies of the variant allele
present, 0, 1 or 2.
lambda
A number controlling the smoothness of the fused
quantile regression (default 15).
rng.seed
The seed used for the random number generator (default
172719943) for reproducibility of simulated equally admixed individuals.
Details
eila is an function for inferring local ancestry.
The admixed samples are assumed as descended from ancestry 1
ancestry 2, or ancestry 3. The data matrixes of admixed samples and
ancestral samples are coded as thee number of copies of the variant
allele present (0, 1, or 2). The physical positions of SNPs are in
base pairs unit.
The method for efficient inference of local ancestry (EILA) in admixed
individuals is based on three steps. The first step assigns a
numerical score (with a range of 0 to 1) to genotypes in admixed
individuals in order to better quantify the closeness of the SNPs to a
certain ancestral population. The second step uses fused quantile
regression to identify breakpoints of the ancestral haplotypes. In the
third step, the k-means classifier is used to infer ancestry at
each locus.
The major strength of EILA is that it relaxes the assumption of
linkage equilibrium and uses all genotyped SNPs rather than only
unlinked loci to increase the power of inference. Another important
strength of this method is its higher accuracy and lower variation.
Value
local.ancestry
The inferred local ancestry matrix with the same
dimensions of admixed. The elements of the matrix are local
ancestry being coded as alleles identification from ancestries 1, 2, or
3. For example, element 12 means one allele is from ancestry 1
and the other allele is from ancestry 2.
rng.seed
The seed used to call set.seed for reproducibility.
rng.state
Prior to the call to set.seed,
rng.state is the value of .Random.seed should
.Random.seed exist. Otherwise, NULL is returned.
Author(s)
James J. Yang, Jia Li, Anne Buu, and L. Keoki Williams
References
Yang, J. J., LI, J., Buu, A., and Williams, L. K. (2013) Efficient
Inference of Local Ancestry. Bioinformatics. doi: 10.1093/bioinformatics/btt488
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(EILA)
Loading required package: class
Loading required package: quantreg
Loading required package: SparseM
Attaching package: 'SparseM'
The following object is masked from 'package:base':
backsolve
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/EILA/eila.Rd_%03d_medium.png", width=480, height=480)
> ### Name: eila
> ### Title: A function to infer local ancestry
> ### Aliases: eila
> ### Keywords: local ancestry quantile regression k-means
>
> ### ** Examples
>
> ## Two ancestries
> data(ceuyri)
> res.eila <- eila(admixed = ceuyri$admixed,
+ position = ceuyri$position,
+ anc1 = ceuyri$anc1,
+ anc2 = ceuyri$anc2)
> cat("Overall accuracy:", mean((res.eila$local.ancestry ==
+ ceuyri$true.local.ancestry), na.rm=TRUE),"\n")
Overall accuracy: 0.9606667
>
> ## Three ancestries
> ## Not run:
> ##D data(ceuchdyri)
> ##D res.eila <- eila(admixed = ceuchdyri$admixed,
> ##D position = ceuchdyri$position,
> ##D anc1 = ceuchdyri$anc1,
> ##D anc2 = ceuchdyri$anc2,
> ##D anc3 = ceuchdyri$anc3)
> ##D cat("Overall accuracy:", mean(res.eila$local.ancestry ==
> ##D ceuchdyri$true.local.ancestry),"\n")
> ## End(Not run)
>
>
>
>
>
> dev.off()
null device
1
>