radmixture

This is an introduction to radmixture which could help you with estimating individual ancestries from large SNP genotype data.

This document introduces you how to use this package.

Installation

• Install the latest development version from GitHub with

  devtools::install_github("wegene-llc/radmixture")

• Install the latest version on CRAN with

  install.packages("radmixture")

  First, you must prepare your raw data file as follow:

and read it into R with read.table or read.csv.

library(radmixture)
genotype <- read.table(file = '/path/to/file')
# genotype <- read.csv(file = 'path/to/file')

Calculate your ancestry components with public dataset

Pay attention:

Since the public datasets are not on CRAN, if you download this package from CRAN, you should download the datasets that you need from GitHub by yourself. For example:

download.file(url = 'https://github.com/wegene-llc/radmixture/raw/master/data/globe4.alleles.RData', destfile = '/path/to/globe4.alleles.RData')
download.file(url = 'https://github.com/wegene-llc/radmixture/raw/master/data/globe4.4.F.RData', destfile = '/path/to/globe4.4.F.RData')

And then, load them into R.

load('/path/to/globe4.alleles.RData')
load('/path/to/globe4.4.F.RData')

Example

Six public datasets could be used in this package.

• Use tfrdpub()to transfer your raw data to a format understood by radmixture

  # Use K4
  res <- tfrdpub(genotype, 4, globe4.alleles, globe4.4.F)
  # Use K7b
  res <- tfrdpub(genotype, 7, K7b.alleles, K7b.7.F)
  # Use world9
  res <- tfrdpub(genotype, 9, world9.alleles, world9.9.F)
  # Use E11
  res <- tfrdpub(genotype, 11, e11.alleles, e11.11.F)
  # Use K12b
  res <- tfrdpub(genotype, 12, K12b.alleles, K12b.12.F)
  # Use K13
  res <- tfrdpub(genotype, 13, globe13.alleles, globe13.13.F)

• Use fFixQN() to calculate your result

  # Use K4
  ances <- fFixQN(res$g, res$q, res$f, tol = 1e-4, method = "BR", pubdata = "K4")
  # Use K7b
  ances <- fFixQN(res$g, res$q, res$f, tol = 1e-4, method = "BR", pubdata = "K7b")
  # Use world9
  ances <- fFixQN(res$g, res$q, res$f, tol = 1e-4, method = "BR", pubdata = "World9")
  # Use E11
  ances <- fFixQN(res$g, res$q, res$f, tol = 1e-4, method = "BR", pubdata = "E11")
  # Use K12b
  ances <- fFixQN(res$g, res$q, res$f, tol = 1e-4, method = "BR", pubdata = "K12b")
  # Use K13
  ances <- fFixQN(res$g, res$q, res$f, tol = 1e-4, method = "BR", pubdata = "K13")

  ances$q is your result.

References

• D.H. Alexander, J. Novembre, and K. Lange. Fast model-based estimation of ancestry in unrelated individuals. Genome Research, 19:1655–1664, 2009.
• H. Zhou, D. H. Alexander, and K. Lange. A quasi-Newton method for accelerating the convergence of iterative optimization algorithms. Statistics and Computing, 2009.

Contributions

We welcome contributions on radmixture. You can fork this repo and make your changes and submit a pull request. Report bug issues on issue page.

License

MIT + LICENSE

TODO

• add tutorial