multiple call type detectors as described in
methods, parallel, randomForest (>= 4.6), rfPermute (>= 2.5),
rlang, stats, swfscMisc (>= 1.5), tibble (>= 3.1.2), tidyr (>=
Packaged: 2021-10-01 21:02:33 UTC; ericarcher

methods, parallel, randomForest (>= 4.6), rfPermute (>= 2.5.1),
Packaged: 2022-03-13 21:58:33 UTC; ericarcher

Title: Download Data from the Bank of Mexico
Description: Provides functions to scrape IQY calls to Bank of Mexico,
downloading and ordering the data conveniently.
Packaged: 2016-08-17 13:39:01 UTC; eduardoflores

Package: bapred
Type: Package
Title: Batch Effect Removal (in Phenotype Prediction using Gene Data)
Version: 0.1
Date: 2015-09-03
Author: Roman Hornung, David Causeur
Maintainer: Roman Hornung <hornung@ibe.med.uni-muenchen.de>
Depends: R (>= 3.1.0), glmnet, lme4, MASS, sva
Imports: FNN, fuzzyRankTests, mnormt
Description: Various tools dealing with batch effects, in particular enabling the
removal of discrepancies between training and test sets in prediction scenarios.
The following batch effect removal methods are implemented: FAbatch, ComBat, (f)SVA,
mean-centering, standardization, Ratio-A and Ratio-G. For each of these we provide
an additional function which enables a posteriori ('addon') batch effect removal
in independent batches ('test data'). Here, the (already batch effect adjusted)
training data is not altered. For evaluating the success of batch effect adjustment
several metrics are provided. Moreover, the package implements a plot for the
visualization of batch effects using principal component analysis. The main functions
of the package are ba() and baaddon() which enable batch effect removal and addon
batch effect removal, respectively, with one of the seven methods mentioned above.
Another important function is bametric() which is a wrapper function for all implemented
methods for evaluating the success of batch effect removal.
License: GPL-2
Encoding: UTF-8
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-09-04 09:25:48

Package: bapred
Type: Package
Title: Batch Effect Removal (in Phenotype Prediction using Gene Data)
Version: 0.2
Date: 2015-12-02
Author: Roman Hornung, David Causeur
Maintainer: Roman Hornung <hornung@ibe.med.uni-muenchen.de>
Depends: R (>= 3.1.0), glmnet, lme4, MASS, sva
Imports: FNN, fuzzyRankTests, mnormt
Description: Various tools dealing with batch effects, in particular enabling the
removal of discrepancies between training and test sets in prediction scenarios.
The following batch effect removal methods are implemented: FAbatch, ComBat, (f)SVA,
mean-centering, standardization, Ratio-A and Ratio-G. For each of these we provide
an additional function which enables a posteriori ('addon') batch effect removal
in independent batches ('test data'). Here, the (already batch effect adjusted)
training data is not altered. For evaluating the success of batch effect adjustment
several metrics are provided. Moreover, the package implements a plot for the
visualization of batch effects using principal component analysis. The main functions
of the package are ba() and baaddon() which enable batch effect removal and addon
batch effect removal, respectively, with one of the seven methods mentioned above.
Another important function is bametric() which is a wrapper function for all implemented
methods for evaluating the success of batch effect removal.
License: GPL-2
Encoding: UTF-8
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-12-03 01:04:15