Access pre-trained preeclampsia models from eoPredData + ExperimentHub
eoPredData 0.99.12
eoPredDataWe hope that eoPredData will be useful for your research. Please use the following information to cite the package and the overall approach. Thank you!
## Citation info
citation("eoPredData")## To cite package 'eoPredData' in publications use:
##
## Boyano I, Yuan V (2024). _eoPredData: ExperimentHub package
## containing model data for predicting preeclampsia status for based on
## plcaental DNA methylation profile_. doi:10.18129/B9.bioc.eoPredData
## <https://doi.org/10.18129/B9.bioc.eoPredData>, R package version
## 0.99.12, <https://bioconductor.org/packages/eoPredData>.
##
## A BibTeX entry for LaTeX users is
##
## @Manual{,
## title = {eoPredData: ExperimentHub package containing model data for predicting preeclampsia status for based on plcaental DNA methylation profile},
## author = {Iciar Boyano and Victor Yuan},
## year = {2024},
## note = {R package version 0.99.12},
## url = {https://bioconductor.org/packages/eoPredData},
## doi = {10.18129/B9.bioc.eoPredData},
## }eoPredDataInstall the R packages ExperimentHub:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("ExperimentHub")
BiocManager::install("mixOmics")There are 2 objects associated with eoPredData:
EHEH8090 Pre-trained model object using mixOmics. This model object can be used to create predictions on DNA methylation profiles collected from placental samples. Details on training and validation are described in
(Boyano and Yuan, 2024).
EHEH8403 Placental DNA methylation test data (49 samples, 452 453 CpGs), used to demonstrate prediction of preeclampsia status using eoPred model. A matrix [cpg x sample].
library(ExperimentHub)
eh <- ExperimentHub()
query(eh, "eoPredData")
library(mixOmics)
# model object
eoPredModel <- eh[['EH8090']]
# test object
x_test <- eh[['EH8403']]
dim(x_test) # 452,453 by 49
x_test <- x_test[rownames(x_test) %in% colnames(eoPredModel$X),]
dim(x_test) # 341,281 by 49
# code to predict on x_test
predictions <- predict(eoPredModel, t(x_test), dist = "max.dist")R session information.
## R Under development (unstable) (2024-10-21 r87258)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.1 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.21-bioc/R/lib/libRblas.so
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## time zone: America/New_York
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] RefManageR_1.4.0 BiocStyle_2.33.1
##
## loaded via a namespace (and not attached):
## [1] httr_1.4.7 cli_3.6.3 knitr_1.48
## [4] rlang_1.1.4 xfun_0.48 stringi_1.8.4
## [7] generics_0.1.3 jsonlite_1.8.9 glue_1.8.0
## [10] backports_1.5.0 plyr_1.8.9 htmltools_0.5.8.1
## [13] sass_0.4.9 rmarkdown_2.28 evaluate_1.0.1
## [16] jquerylib_0.1.4 fastmap_1.2.0 yaml_2.3.10
## [19] lifecycle_1.0.4 bookdown_0.41 stringr_1.5.1
## [22] BiocManager_1.30.25 compiler_4.5.0 Rcpp_1.0.13
## [25] timechange_0.3.0 bibtex_0.5.1 digest_0.6.37
## [28] R6_2.5.1 magrittr_2.0.3 bslib_0.8.0
## [31] tools_4.5.0 lubridate_1.9.3 xml2_1.3.6
## [34] cachem_1.1.0[1] I. Boyano and V. Yuan. eoPredData: ExperimentHub package containing model data for predicting preeclampsia status for based on plcaental DNA methylation profile. R package version 0.99.12. 2024. DOI: 10.18129/B9.bioc.eoPredData. URL: https://bioconductor.org/packages/eoPredData.