View source: R/normalize_batch.R
compare_surrogate_estimates | R Documentation |
This is entirely derivative, but seeks to provide similar estimates for one's own actual data and catch corner cases not taken into account in that document (for example if the estimators don't converge on a surrogate variable). This will attempt each of the surrogate estimators described by Leek: pca, sva supervised, sva unsupervised, ruv supervised, ruv residuals, ruv empirical. Upon completion it will perform the same limma expression analysis and plot the ranked t statistics as well as a correlation plot making use of the extracted estimators against condition/batch/whatever else. Finally, it does the same ranking plot against a linear fitting Leek performed and returns the whole pile of information as a list.
compare_surrogate_estimates(
expt,
extra_factors = NULL,
filter_it = TRUE,
filter_type = TRUE,
do_catplots = FALSE,
surrogates = "be",
...
)
expt |
Experiment containing a design and other information. |
extra_factors |
Character list of extra factors which may be included in the final plot of the data. |
filter_it |
Most of the time these surrogate methods get mad if there are 0s in the data. Filter it? |
filter_type |
Type of filter to use when filtering the input data. |
do_catplots |
Include the catplots? They don't make a lot of sense yet, so probably no. |
surrogates |
Use 'be' or 'leek' surrogate estimates, or choose a number. |
... |
Extra arguments when filtering. |
List of the results.
[normalize_expt()] [plot_pca()] [all_adjuster()] [corrplot] [ffpe]
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