quickmap()
. Removed all additional processing,
threshold setting, and value clipping except for optional variance removal.
The function now simply relays arguments to pheatmap::pheatmap()
. edger_to_df()
return unsorted results. this is useful for returning
results back in the same order that they are present in the original objecttheme_coriell()
theme_coriell()
to drop panel borders and removed angle from x-axis
text. plot_volcano()
and plot_md()
defaults to use unaliased points,
smaller text sizes for labels, and moved labels further to the sides. pairwise_intersections()
. plot_cor_pairs()
panther_go()
to include the reference gene list when performing over representation testing. There may still be
bugs here.plot_volcano()
and plot_md()
to allow setting axis
limits prior to determining annotation placement. These functions now also use
theme_coriell()
by default.meta_de()
function to operate strictly on SummarizedExperiment objects. This function is significantly faster than the previous version.dfs2se()
to convert a list of data.frames to a SummarizedExperiment object for use by meta_de()
jackknifeSE()
.meta_vote()
, meta_pcombine()
and
plot_metavolcano()
, in favor of the newer meta_de()
function which
provides an interface to metapod
for combining p-values in a more robust way.quickmap()
when calculating breaks and
made some changes to the way the fix_extreme
argument behaves.panther_go()
to use httr2
UMAP()
and plot_umap()
functions. The UMAP()
functions accepts
PCA objects from PCAtools
, prcomp
, or a distance matrix or raw data matrix
and exposes the umap.defaults
as function arguments. plot_umap()
function provides a simple plotting method for the
data.frame produced by the UMAP()
function.quickmap()
function. Avoid pheatmap
scaling in
favor of vectorized scaling. Speed up removeVar calculations with
Rfast::rowVars()
or matrixStats::rowVars()
if available. Speed up
clustering and distance matrix calculations by performing distance matrix
calculations with rdist::rdist()
and clustering with fastcluster::hclust()
if available. Round values in fix_extreme to better maintain original scale
limits.plot_boxplot()
, plot_density()
, and
plot_parallel()
. These functions are now generics that work with matrix,
data.frame, and SummarizedExperiment
classesplot_volcano()
and plot_md()
. For
plot_volcano()
set the default value for the labels to NULL and removed the
removed the labels altogether for plot_md()
plot_boxplot()
,
plot_density()
, and plot_parallel()
theme_coriell()
plot_volcano()
and plot_md()
to have consistent colorsquickmap()
that removes low variance features before
plotting.pairwise_fisher_test()
quickmap()
to enable fixing the colors at the extreme ends
of the data.plot_volcano()
and plot_md()
rarefy()
function. Replaces subsample_counts()
read_bismark()
that reads in a list of Bismark coverage files
and optionally filters by coverage and variance.plot_md()
, plot_volcano()
, and summarize_dge()
to remove dplyr()
dependency.
The changes to these functions are breaking. Arguments for column names must now be quoted.plot_volcano()
and plot_md()
now support additional arguments for modifying the point
size, shape, and color. See function documentation.process_quant_file()
function. Switched to using tximport()
in all
pipelines.MetaVolcanoR
but are much faster. meta_vote()
function implements a vote-counting strategy for determining
common differentially expressed genesmeta_pcombine()
function combines p-values and logFCs across studies.plot_metavolcano()
function provides a plotting function specific to the
meta_vote()
results.magittr
pipe. Now coriell
doesn't export the pipe.edger_to_df()
returns a data.frame instead of a tibbledistinct_rgb_palette()
and random_rgb_palette()
rank_threshold()
.
Inspired by unimodal thresholding algorithm from image analysis.panther_go()
now returns a data.table
of the raw, unlisted data returned from
the request. The original version pivoted the table wider using columns for the
GO term and the description of the GO term. This result gave inaccurate results
when using a different pathway in the function call. data.table()
.permutation_correlation_test()
that applies permuted
vector in a vectorized fashion over the entire matrix. edger_to_df()
to allow for any EdgeR
results objects to be used as input.Add the following code to your website.
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