High-Performance Open-Source Archive
confint() with deconv
objects to allow calculation of confidence intervals.max_similarity() for calculating maximum similarity
between cell types.deconvolute() [experimental].$opt element to store call arguments in
deconvolute().plot_comp() and plot_path() with
option to show cell percentages.deconvolute() to help with
issue #20.tune_deconv().plot_tunevar() to compare MSE, bias^2 and
variance.kappa() to compute the condition
number of the spillover matrix.plot_path() to show how the coefficient paths vary
with compensation for either a single bulk sample or a cell
subclass.plot_pred() as an alternative to
plot_set() for viewing predicted vs observed results from
simulations in a single correlation plot.zero_fraction argument to
generate_samples().nest_outputdeconvolute().lambda to
deconvolute() [experimental].resvar metric to tune_deconv() to
examine residual variance of bulk gene expression.deconvolute() no longer returns se and
hat in the subclass list element. Standard
errors can be obtained with the new function se().cores argument has been removed from
deconvolute()mclapply(). The problem is isolated to R
4.5.2 arm64 for macOS on M* Macs; or any version of R for macOS
including intel, if vecLib BLAS is being used via a symlink. The
solution is to use cores = 1 with
deconvolute() and tune_deconv() whenever
vecLib BLAS is in use.pbmcapply::pbmclapply() as this caused
problems with R 4.5.2 for macOS arm64 (Apple M* Macs) even with
cores=1. This fixes indefinite hanging in
tune_deconv() associated with vecLib BLAS.log argument in deconvolute() to
logged_bulk. NB. this is a change of logic.residuals.deconv() to allow recalculation of full
residuals matrix.mergeMarkers() if cellMarkers object has no
cell grouping vector.cat() to message()tune_deconv()
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