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R package to correct measurement biases in gene methylation analyses

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rBiasCorrection

CRAN Status Badge CRAN Checks Dependencies R CMD Check via {tic} linting test-coverage codecov

rBiasCorrection is published in 'BiasCorrector: fast and accurate correction of all types of experimental biases in quantitative DNA methylation data derived by different technologies' (2021) in the International Journal of Cancer (DOI: https://onlinelibrary.wiley.com/doi/10.1002/ijc.33681).

rBiasCorrection is the R implementation with minor modifications of the algorithms described by Moskalev et al. in their research article 'Correction of PCR-bias in quantitative DNA methylation studies by means of cubic polynomial regression', published 2011 in Nucleic acids research, Oxford University Press (DOI: https://doi.org/10.1093/nar/gkr213).

Installation

CRAN version

You can install rBiasCorrection simply with via R's install.packages interface:

install.packages("rBiasCorrection")

Development version

If you want to use the latest development version, you can install the github version of rBiasCorrection with:

install.packages("remotes")
remotes::install_github("kapsner/rBiasCorrection")

Example

This is a basic example which shows you how to correct PCR-bias in quantitative DNA methylation data:

library(rBiasCorrection)

# define input file paths
experimental <- file.path(tempdir(), "/experimental_data.csv")
calibration <- file.path(tempdir(), "/calibration_data.csv")

# create example files from provided example dataset
data.table::fwrite(
  rBiasCorrection::example.data_experimental$dat,
  experimental
)
data.table::fwrite(
  rBiasCorrection::example.data_calibration$dat,
  calibration
)

# run bias correction algorithm
biascorrection(
  experimental = experimental,
  calibration = calibration,
  samplelocusname = "BRAF"
)

More detailed information on how to use the package rBiasCorrection can be found in the vignette and the FAQs.

BiasCorrector

The GUI BiasCorrector provides the functionality implemented in rBiasCorrection in a web application. For further information please visit https://github.com/kapsner/BiasCorrector.

FAQ

For further information, please refer to the frequently asked questions.

Citation

L.A. Kapsner, M.G. Zavgorodnij, S.P. Majorova, A. Hotz‐Wagenblatt, O.V. Kolychev, I.N. Lebedev, J.D. Hoheisel, A. Hartmann, A. Bauer, S. Mate, H. Prokosch, F. Haller, and E.A. Moskalev, BiasCorrector: fast and accurate correction of all types of experimental biases in quantitative DNA methylation data derived by different technologies, Int. J. Cancer. (2021) ijc.33681. doi:10.1002/ijc.33681.

@article{kapsner2021,
  title = {{{BiasCorrector}}: Fast and Accurate Correction of All Types of Experimental Biases in Quantitative {{DNA}} Methylation Data Derived by Different Technologies},
  author = {Kapsner, Lorenz A. and Zavgorodnij, Mikhail G. and Majorova, Svetlana P. and Hotz-Wagenblatt, Agnes and Kolychev, Oleg V. and Lebedev, Igor N. and Hoheisel, J{\"o}rg D. and Hartmann, Arndt and Bauer, Andrea and Mate, Sebastian and Prokosch, Hans-Ulrich and Haller, Florian and Moskalev, Evgeny A.},
  year = {2021},
  month = may,
  pages = {ijc.33681},
  issn = {0020-7136, 1097-0215},
  doi = {10.1002/ijc.33681},
  journal = {International Journal of Cancer},
  language = {en}
}

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R package to correct measurement biases in gene methylation analyses

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