Package: causalBatch 1.4.0
causalBatch: Causal Batch Effects
Software which provides numerous functionalities for detecting and removing group-level effects from high-dimensional scientific data which, when combined with additional assumptions, allow for causal conclusions, as-described in our manuscripts Bridgeford et al. (2024) <doi:10.1101/2021.09.03.458920> and Bridgeford et al. (2023) <doi:10.48550/arXiv.2307.13868>. Also provides a number of useful utilities for generating simulations and balancing covariates across multiple groups/batches of data via matching and propensity trimming for more than two groups.
Authors:
causalBatch_1.4.0.tar.gz
causalBatch_1.4.0.zip(r-4.5)causalBatch_1.4.0.zip(r-4.4)causalBatch_1.4.0.zip(r-4.3)
causalBatch_1.4.0.tgz(r-4.5-any)causalBatch_1.4.0.tgz(r-4.4-any)causalBatch_1.4.0.tgz(r-4.3-any)
causalBatch_1.4.0.tar.gz(r-4.5-noble)causalBatch_1.4.0.tar.gz(r-4.4-noble)
causalBatch_1.4.0.tgz(r-4.4-emscripten)causalBatch_1.4.0.tgz(r-4.3-emscripten)
causalBatch.pdf |causalBatch.html✨
causalBatch/json (API)
# Install 'causalBatch' in R: |
install.packages('causalBatch', repos = c('https://neurodata.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/neurodata/causal_batch/issues
Last updated 14 days agofrom:b73e581699. Checks:9 ERROR. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | FAIL | Mar 20 2025 |
R-4.5-win | ERROR | Mar 20 2025 |
R-4.5-mac | ERROR | Mar 20 2025 |
R-4.5-linux | ERROR | Mar 20 2025 |
R-4.4-win | ERROR | Mar 20 2025 |
R-4.4-mac | ERROR | Mar 20 2025 |
R-4.4-linux | ERROR | Mar 20 2025 |
R-4.3-win | ERROR | Mar 20 2025 |
R-4.3-mac | ERROR | Mar 20 2025 |
Exports:cb.align.kway_matchcb.align.vm_trimcb.correct.aipw_cComBatcb.correct.apply_aipw_cComBatcb.correct.apply_cComBatcb.correct.matching_cComBatcb.detect.caus_cdcorrcb.sims.cate.heteroskedastic_simcb.sims.cate.kclass_sigmoidal_simcb.sims.cate.nonmonotone_simcb.sims.cate.sigmoidal_simcb.sims.sim_impulsecb.sims.sim_impulse_asycovcb.sims.sim_linearcb.sims.sim_sigmoid
Dependencies:annotateAnnotationDbiaskpassbackportsBHBiobaseBiocGenericsBiocParallelBiostringsbitbit64blobbootcachemcdcsischkclicodetoolscpp11crayoncubaturecurlDBIdplyredgeRfansifastmapFNNformatRfutile.loggerfutile.optionsgenefiltergenericsGenomeInfoDbGenomeInfoDbDatagluehttrIRangesjsonliteKEGGRESTkernlabKernSmoothkslambda.rlatticelifecyclelimmalocfitmagrittrMASSMatchItMatrixMatrixGenericsMatrixModelsmatrixStatsmclustmemoisemgcvmimemulticoolmvtnormnlmennetnpopensslpillarpkgconfigplogrpngpracmaquadprogquantregR6RcppRcppProgressrlangRSQLiteS4VectorssnowSparseMstatmodsurvivalsvasystibbletidyselectUCSC.utilsutf8vctrswithrXMLxtableXVector
Readme and manuals
Help Manual
Help page | Topics |
---|---|
K-Way matching | cb.align.kway_match |
Vector Matching | cb.align.vm_trim |
Augmented Inverse Probability Weighting Conditional ComBat | cb.correct.aipw_cComBat |
Fit AIPW ComBat model for batch effect correction | cb.correct.apply_aipw_cComBat |
Adjust for batch effects using an empirical Bayes framework | cb.correct.apply_cComBat |
Matching Conditional ComBat | cb.correct.matching_cComBat |
Causal Conditional Distance Correlation | cb.detect.caus_cdcorr |
Simulate Data with Heteroskedastic Conditional Average Treatment Effects | cb.sims.cate.heteroskedastic_sim |
K-class Sigmoidal CATE Simulation | cb.sims.cate.kclass_sigmoidal_sim |
Non-monotone CATE Simulation | cb.sims.cate.nonmonotone_sim |
Sigmoidal CATE Simulation | cb.sims.cate.sigmoidal_sim |
Impulse Simulation | cb.sims.sim_impulse |
Impulse Simulation with Asymmetric Covariates | cb.sims.sim_impulse_asycov |
Linear Simulation | cb.sims.sim_linear |
Sigmoidal Simulation | cb.sims.sim_sigmoid |