BiasCorrector 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).
BiasCorrector is the user friendly implementation 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).
-
Make sure, you have R installed on your system:
-
Then open your development environment and install this R package:
You can install BiasCorrector simply with via R’s install.packages
interface:
install.packages("BiasCorrector")If you want to use the latest development version, you can install the
github version of BiasCorrector with:
install.packages("remotes")
remotes::install_github("kapsner/BiasCorrector")- To start BiasCorrector, just run the following command in R. A browser tab should open displaying BiasCorrector. Alternatively you can type the URL “localhost:3838/” in your browser.
library(BiasCorrector)
launch_app()To simplify installation an deployment of BiasCorrector you can clone
this repository and build your own docker image. Make sure, you have
Docker and docker-compose installed on your system.
# clone the repository
git clone https://github.com/kapsner/BiasCorrector
# go to the docker subfolder
cd BiasCorrector/docker/
# run the build script
./build_image.sh
# when the building is finished, just start the container by running
docker-compose -f docker-compose.local.yml up -d# clone the repository
git clone https://github.com/kapsner/BiasCorrector
# go to the docker subfolder
cd BiasCorrector/docker/
# start the Docker container
docker-compose -f docker-compose.remote.yml up -dType the URL “localhost:3838/” in your browser and start working with
BiasCorrector.
BiasCorrector depends on the rBiasCorrection R-package, which is the
implementation of the core functionality to correct measurement biases
in DNA methylation analyses. BiasCorrector brings this functionality
to a user-friendly shiny web application.
rBiasCorrection is available at
https://github.com/kapsner/rBiasCorrection.
A video tutorial describing the workflow of how to use BiasCorrector
in order to correct measurement bias in DNA methylation data is
available on youtube.
A demo version of BiasCorrector is available
here.
More detailed information on how to use the backend-package
rBiasCorrection can be found in its
vignette.
The FAQs can be found
here.
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}
}- Original work by Moskalev et al.: https://doi.org/10.1093/nar/gkr213
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