SCpubr::package_report(extended = TRUE)
to get an overview of the missing dependencies.do_WafflePlot()
: This function displays proportions as a pictogram grid of 10x10 tiles. It helps to visually see at a glance the proportions of your data. This fails to correctly convey decimal proportions and completely ignores heavily under-represented classes in your dataset. do_RankedExpressionPlot()
to plot expression values as a heatmap along a diffusion component.do_FunctionalAnnotationPlot()
.do_GroupedGOTermPlot()
.The reason behind it is that they, together with do_TermEnrichmentPlot() targetted the same analysis and, therefore, were redundant.
do_DiffusionMapPlot()
is now called do_RankedEnrichmentPlot()
. As it now accepts any dimensional reduction and not only diffusion maps.do_TermEnrichmentPlot()
: Recoded the whole function. Now accepts the result of using clusterProfiler::enrichGO()
, clusterProfiler::enrichKEGG()
, etc. The output is a dot plot with the terms on the Y axis, the Gene Ratio in the X, colored by the adjusted p-value and size mapped to the Gene Count.do_DotPlot()
: Removed dependencies with Seurat::DotPlot()
.do_RankedEnrichmentPlot()
, do_EnrichmentHeatmap()
and do_SCEnrichmentHeatmap()
do not longer accept flavor = "AUCell"
due to dependency issues and lack of development support.The reason of these modification is to allow for a much clearer and concise output than before.
ggalluvial
to deal with deprecation of functions from dplyr
and tidyr
that were still used in ggalluvial
functions.legend.ncol
, legend.nrow
and legend.byrow
parameters to control legend behavior.map_signif_levels
would only accept a logical and not custom mappings.map_signif_levels
is used, the mapping now appears as a plot legend for clarity.include_chr_arms
parameter to decide whether the heatmap should include a breakdown of the arms or just keep it by chromosomes.cells.highlight
with only one cell.split.by
and group.by
to have a different size than the rest of panels when ncol
parameter was also used.cells.highlight
and idents.highlight
. group.by
or split.by
depending of the usage context.split.by.combined
parameter and set its default value to TRUE
. This allows to toggle on or off whether to display the combined view when split.by
is used.split.by
is used alongside group.by
, it is now enforced to show the combined plot (split.by.combined = TRUE
), to avoid bugs.legend.dot.border
parameter to select whether we want a black border around the legend dots or not.font.family
would not be applied when label = TRUE
. (#76)dot.scale
to 8.colors.use
, which had no effect as of previous version but was still listed as parameter.Seurat::DotPlot()
. This means that there will be some differences with the output of this function. However, this is a design choice for the sake of preventing future dependency problems.split.by
parameter.features
is provided as a named list, the plot facets them based on the belonging list (duplcated genes are removed). Cannot be used alongside split.by
.scale
and scale.by
parameters. In the sense of how they worked in Seurat
.zscore.data
parameter. When set to TRUE
, it computes Z-scores for each gene across the different groups, allowing for inspection of which group has highest or lowest expression, but prevents you from comparing values across different genes. It is intended to be used alongside slot = "data"
. split.by
parameter.dot_border
. This is a design choice of SCpubr
.scale_scores
to FALSE
.scale_scores = TRUE
.scale_scores = TRUE
and features.order
would trigger an error since the output had the suffix _scaled
on it. This has been patched.font.family
would not be applied when label = TRUE
. (#76)top_interactions_by_group
which when set to TRUE
will report for each pair of source
and target
, as many interactions as stated in top_interactions
.size = 1.25
aesthetic from the call to ggridges::geom_ridge...
.order
parameter to reorder the groups based on the median. Only works when split.by
is set to NULL
.split.by
.use_labels = TRUE
in combination with order_tabs_by = "both"
.GetAssayData
and SetAssayData
functions.YlGnBu
.feature_to_rank
if continous_feature = TRUE
. sequential.direction
to 1
. legend.position
to bottom
when continuous_feature = FALSE
. legend.position
to bottom
. use_silhouette = TRUE
. min.cutoff
or max.cutoff
would render the values outside these bounds to NA and therefore being plotted as grey. Now they will have the highest/lowest value possible.symmetry.type
parameter, that allows to control how the symmetry is computed: either in absolute values (taking into account the highest and lowest value) or in the middle point specified by symmetry.center
.symmetry.center
parameter, that allows to control the center of symmetry when symmetry.type
is set to centered
. legend.position
to bottom
. plot_boxplots = FALSE
.legend.title.position
parameter and set it up as top
by default.SCpubr::check_dependencies()
to support the use of SCpubr::package_report()
. SCpubr::do_EnrichmentHeatmap
This major update focus on a complete re-implementation of all heatmap-based functions into ggplot2
instead of ComplexHeatmap
. This will lead to many of the existing code to break. The trade-off between the difficulty of debug, expand and maintain the existing heatmap-based functions with regards to the capabilities ComplexHeatmap offers with regards to ggplot2 was not worthy.
All heatmap-specific parameters have been replaced with the overarching parameters that are used across functions. This decision was taking after a lot of thought, but ultimately, having all plots rely on ggplot2 makes it way more compatible to work with them together, to debug, and to further implement new ideas.
Many (except a few selected cases) of the functions that returned list of different plots have been modified to return a single (and most important/relevant) plot and the option to return the Seurat object with the data generated added to it has been implemented so that the user can still generate plots with it. This goes in line with the fact that having so many interconnected functions made it very difficult to expand on them, if needed, as the downstream effects will cascade to other functions as well.
viridis_color_map
to viridis.palette
.viridis_direction
to viridis.direction
.sequential_direction
to sequential.direction
.rotate_x_axis_labels
to axis.text.x.angle
.rotate_strip_text
to strip.text.angle
.SCpubr::do_MetadataPlot()
to generate metadata heatmaps with ease both from Seurat object or from a data frame. Will be first released as part of the development version
and then released in CRAN as part of future updates. The idea is to gather feedback from users before officially releasing it.SCpubr::do_SCExpressionHeatmap()
to generate heatmaps of expression of genes across all cells in the dataset. Will be first released as part of the development version
and then released in CRAN as part of future updates. The idea is to gather feedback from users before officially releasing it.SCpubr::do_SCEnrichementHeatmap()
to generate heatmaps of enrichment of genes across all cells in the dataset. Will be first released as part of the development version
and then released in CRAN as part of future updates. The idea is to gather feedback from users before officially releasing it.SCpubr::do_AffinityAnalysisPlot()
to assess the affinity of gene sets to subset of cells in the Seurat objects using the weighted means algorithms from DecoupleR. Will be first released as part of the development version
and then released in CRAN as part of future updates. The idea is to gather feedback from users before officially releasing it.SCpubr::do_LoadingsPlot()
to generate a summary heatmap of the PCA loadings (top and bottom scored genes for each PC) together with a expression heatmap of the same genes. Will be first released as part of the development version
and then released in CRAN as part of future updates. The idea is to gather feedback from users before officially releasing it.SCpubr::do_DiffusionMapPlot()
to analyze the output of a diffusion map analysis on the context of enrichment in gene sets used for the generation of the diffusion map. Will be first released as part of the development version
and then released in CRAN as part of future updates. The idea is to gather feedback from users before officially releasing it.SCpubr::check_dependencies()
to generate a per-function summary of the needed packages to run the function. The report has been enhanced with cli
package and now clearly illustrates what is missing to run the function.SCpubr::do_SankeyPlot()
has been removed and replaced by SCpubr::do_AlluvialPlot()
, which is present in the official CRAN versions.SCpubr::do_PseudotimePlot()
has been removed indefinitely until a better, revamped, state-of-the-art version is generated.SCpubr::do_AzimuthAnalysisPlot()
has been removed as the output can be accomplished by a combination of the current functions in SCpubr
. A vignette will be added to reproduce the same analysis.min.cutoff
or max.cutoff
, the legend will show that the min/max value is higher/lower than the one provided, if such value appeared originally in the legend breaks. This potentially interacts with enforce_symmetry
.number.breaks
parameter to control the number of breaks in the legend of ggplot2-based plots. It will not always work, as the function will try to fit the breaks accordingly. But still, will give some range of freedom to the user.colorsteps
from legend.type
parameters as it was prone to generate unintended bugs.min.cutoff
and max.cutoff
from NULL
to NA
.diverging.palette
parameter in all plots that have a symmetrical color scale to help selecting other possible color scales for the plot.sequential.palette
parameter in all plots that have a continuous, non-symmetrical color scale to help selecting other possible color scales for the plot, in the case the user does not want to use viridis color scales.SCpubr::state_dependencies()
to SCpubr::check_dependencies()
.cli
package.plot.title.face
: To control the style of the title.plot.subtitle.face
: To control the style of the subtitle.plot.caption.face
: To control the style of the caption.axis.title.face
: To control the style of the axis title.axis.text.face
: To control the style of the axis text.legend.title.face
: To control the style of the legend title.legend.text.face
: To control the style of the legend text.bold
to plain
. bold
to plain
.plot.axes = TRUE
parameter in SCpubr::do_DimPlot()
, SCpubr::do_FeaturePlot()
and SCpubr::do_NebulosaPlot()
, now the entirety of the X and Y axis is removed, titles included.SCpubr::do_DimPlot()
, SCpubr::do_FeaturePlot()
and SCpubr::do_NebulosaPlot()
. SCpubr::do_AlluvialPlot
sequential.palette
and sequential.direction
parameters.SCpubr::do_BarPlot
facet.by
parameter to extra group the bars by a third metadata variable.order.by
to reorder the bars when using position = fill
based on a value in group.by
.group.by
, split.by
and order.by
to those that make sense to plot. For instance, a bar plot using group.by
and position = fill
but not using split.by
resulted in bars of equal lenght with only one value per group of proportion 1
.plot.grid
to FALSE
.add.n
to display the total count on top when position = fill
.add.n.face
to control the appearance of the text displayed.add.n.expand
to control the range of values in the Y axis. This has to be minimum 0 and maximum at least 1. This is set in order to tweak the limits so that the labels fit when flip = TRUE
.SCpubr::do_BeeSwarmPlot
order
parameter to reorder the groups based on the median rank.SCpubr::do_BoxPlot
na.rm
to geom_boxplot
to avoid unnecessary warnings when introducing NAs as part of the data.order
would not work if NAs
are in the data.boxplot.linewidth
from 1
to 0.5
.group.by
and split.by
, the package would check that the colors provided to colors.use
need to match the values in group.by
and not split.by
.SCpubr::do_CorrelationPlot
min.cutoff
and max.cutoff
parameter to add cutoffs to the scales.mode = "jaccard"
to compute a correlation matrix of a list of gene sets based on jaccard similarity.use_viridis
, sequential.palette
and sequential_direction
and diverging.palette
to control color palettes.cluster
parameter to toggle on/off the clustering of the rows and columns in the heatmap.remove.diagonal
parameter to toggle on/off the conversion of the diagonal in the correlation matrix to NA
.min.cutoff
and max.cutoff
. number.breaks
will not work in mode = "jaccard"
.SCpubr::do_CopyNumberVariantPlot()
return_object
has been added to return the Seurat object with a new assay containing the CNV scores per cell on the data
slot of the CNV_scores
assay.SCpubr::do_DimPlot
cells.highlight
or idents.hightlight
or idents.keep
are used. Also removed the "Not selected" item from the legend when doing so, as it was redundant.group.by
and split.by
, given that the individual UMAPs would not have the same number of entities to plot and color.SCpubr::do_DotPlot
scale
parameter to allow for the data to be scaled or not scaled.split.by
parameter in favor or the higher consistency and proper functionality accross parameters. Will probably come in the future, implemented outside of the umbrella of Seurat.cluster.idents
to cluster
.flip
when features
was a list of genes. Now any combination of flip
and features
is possible.SCpubr::do_EnrichmentHeatmap
return_object = TRUE
and plot the enrichment scores separately, that are stored as a new Assay.return_matrix
parameter as the scores can now be retrieved from the Seurat object as an assay.named lists
as input for the function.cluster
parameter to allow for clustering of rows and columns.groups.order
to allow for specifically arrange the groups defined by group.by
with a given order.features.order
to allow for specifically arrange the gene sets defined by input_gene_list
.SCpubr::do_ExpressionHeatmap
cluster
parameter to allow for clustering of rows and columns.groups.order
to allow for specifically arrange the groups defined by group.by
with a given order.features.order
to allow for specifically arrange the features defined by features
.SCpubr::do_FeaturePlot
split.by
, cells.hightlight
and idents.highlight
.border.density
to reduce the amount of extra cells drawn on the background to generate the borders. This will be a number between 0 and 1 corresponding to the quantile of the distribution of density of the points in the scatterplot drawn in the background. The lower the value, the harder it will be to keep a border around all cells, while it will significantly reduce the overall weight of the plot object.group.by
, that allows to plot a big dot in the center of each group designated by group.by
and thus allowing to locate easily where each identity is in the FeaturePlot. Also, plots a legend matching the color of the dots. This can be tweaked with additional parameters such as:group.by.show.dots
to controlw hether these dots are plotted or not (to allow only plotting colored borders around cells - see below).group.by.dot.size
to control the size of the introduced dots.group.by.cell_border
to plot another contour-like border which also displays the color coding of the clusters designated by group.by
, to signal the reach of each cluster. However, this basically signals the cluster the cells in the periphery of the cell blobs belong to. Take that into account.group.by.cell_borders.alpha
controls the alpha of the new cell borders.group.by.legend
controls the legend title of the new legend.split.by.idents
to idents.keep
to better synergize with the parameter in SCpubr::do_DimPlot
. Only works when split.by
is used.SCpubr::do_FunctionalAnnotationPlot
return_matrix
is added, so that the user can use it to compute further analysis or visualizations.SCpubr::do_FunctionalAnnotationPlot
order_by_mean
to order
.order = TRUE
now is done based on the median instead of the mean.SCpubr::do_LigandReceptorPlot()
liana::liana_aggregate()
is taken into account.arrange_interactions_by
as now the function only accepts the output of liana::liana_aggregate()
.sort.by
parameter instead to select how the output of liana::liana_aggregate()
should be ordered prior the subset by top_interactions
. Five modes are available:A
: Orders the output by specificity
.B
: Orders the output by magnitude
.C
: Orders the output by specificity
then magnitude
. This prioritizes the specificity
column.D
: Orders the output by magnitude
then specificity
. This prioritizes the magnitude
column.E
: Orders the output by specificity
and magnitude
providing equal weights to both columns.flip
parameter as the output was prone to errors.compute_ChordDiagrams
and added return_interactions
. This parameter returns two tibbles that can be used alongside SCpubr::do_ChordDiagramPlot
to plot the diagrams. keep_source
and keep_target
takes place before subsetting for the top N interactions defined by top_interactions
. This ensures that, if the user wants to focus on a given interaction subset, we retrieve the most important interactions for the subset.magnitude
and specificity
columns to allow the user to choose which variables to use for plotting.sorting.type.magnitude
and sorting.type.specificity
to allow the user to choose how the columns are sorted prior plotting.invert_magnitude
and invert_specificity
to allow the user to choose how the data is displayed for columns that tend to 0. Inverting performs a -log10
transformation on the column.verbose
parameter and set it to TRUE
by default to inform the user of the arrangements taking place in the output of liana::liana_aggregate()
prior plotting.SCpubr::do_PathwayActivityPlot()
return_object
parameter that returns the Seurat object with the new assay to use for other plotting purposes (such as Geyser and Feature plots).return_object = TRUE
and plot the scores separately.slot
parameter to decide whether to plot scale data or not.enforce_symmetry = FALSE
the color palette used was diverging.palette
instead.SCpubr::do_TFActivityPlot()
return_object
parameter that returns the Seurat object with the new assay to use for other plotting purposes (such as Geyser and Feature plots).return_object = TRUE
and plot the scores separately.slot
parameter to decide whether to plot scale data or not.enforce_symmetry = FALSE
the color palette used was diverging.palette
instead.More hotfixes in unit tests to comply with CRAN checks.
Hotfixes in unit tests to comply with CRAN checks.
element_line
,do_AlluvialPlot()
, do_AzimuthAnalysisPlot()
, do_ExpressionHeatmap()
, do_GroupedGOTermPlot()
and do_FunctionalAnnotationPlot()
.legend.ncol
, legend.nrow
, legend.title
and legend.byrow
to as many functions as possible to further customize legend appearance.SCpubr::do_BeeSwarmPlot()
min.cutoff
and max.cutoff
parameter.viridis_direction
parameter to control how the continuous color scale is formed.return_object
parameter to return the Seurat object with the enrichment scores computed.legend.position
conditional of whether continuous_feature
is set to TRUE. If it is false, legend is not displayed unless the user specifies otherwise.SCpubr::do_BarPlot()
flip
and split.by
.x_lab
and y_lab
would not rotate accordingly when using flip = TRUE
.SCpubr::do_BeeSwarmPlot()
groupOnX
parameter of geom_quarirandom
. This will likely affect users with a lower version.SCpubr::do_BoxPlot()
assay
to NULL and will default to the default assay in the seurat object.SCpubr::do_CellularStatesPlot()
SCpubr::do_CorrelationPlot()
viridis_direction
parameter.SCpubr::do_DimPlot()
legend.title
was used.split.by
works, so that now only one legend is displayed for the whole group and cells have border.label.size
and label.box
parameters for further customize the appearance of the plot when using label = TRUE
.repel
to FALSE
by default.SCpubr::do_EnrichmentHeatmap()
flavor = "AUCell"
, that lets the user compute AUCell scoring of the gene sets.group.by
parameters at the same time.group.by
to be returned properly, leading to the last value of group.by
replacing all the rest.SCpubr::do_FeaturePlot()
label
, label.size
and label.color
parameter to reproduce the same behavior as in Seurat::FeaturePlot()
.SCpubr::do_GroupwiseDEPlot()
assay
to NULL and will default to the default assay in the seurat object.SCpubr::do_LigandReceptorPlot()
arrange_interactions_by
to control how output interactions are arranged (either by aggregate_rank, specificity, magnitude or a combination of magnitude and specificity).sort_interactions_alphabetically
to control whether the output dotplot has the interactions ordered alphabetically or as they come in the original matrix (meaning, they follow the arrangement specified in arrange_interactions_by
). ((liana's issue #72))do_PathwayActivityPlot()
enforce_symmetry
is set to FALSE
, then the color scale turns into a viridis-based one instead of a two-color gradient scale.do_TFActivityPlot()
enforce_symmetry
is set to FALSE
, then the color scale turns into a viridis-based one instead of a two-color gradient scale.SCpubr::do_ViolinPlot()
colors.use
.do_GeyserPlot
with categorical variables had a bug that mapped the legend to the continuous axis.min.cutoff
and max.cutoff
parameter to effectively subset the color scale and remove the effect of extreme outliers in all ComplexHeatmap-based functions.min.cutoff
and max.cutoff
parameter to effectively subset the color scale and remove the effect of extreme outliers in all ggplot2-based functions susceptible to be biased by outliers.SCpubr::do_DimPlot()
split.by
and group.by
in combination, the cells colored on top of the UMAP also have a border.split.by
and group.by
in combination, the extra new layers would not raster if raster = TRUE
.split.by
and group.by
in combination, no plots will appear if ncol
is set.plot_density_contour
.raster.dpi
to Seurat versions higher or equal to 4.1.0.SCpubr::do_EnrichmentHeatmap()
plot_FeaturePlots
and plot_GeyserPlots
to also report the enrichment scores in a gene set-based manner.flavor
parameter, that accepts Seurat
and UCell
to allow for different enrichment scoring methods. It requires R 4.2.0
to run.symmetrical_scale
to enforce_symmetry
to have a greater coherence across functions.SCpubr::do_FeaturePlot()
plot_density_contour
.raster.dpi
to Seurat versions higher or equal to 4.1.0.SCpubr::do_GeyserPlot()
color.by
implementation due to it being very buggy. This will be re-implemented in a future patch.SCpubr::do_RidgePlot()
assay = "RNA"
or, in fact, any other assay rather than SCT
will result in an error.SCpubr::do_ViolinPlot()
split.by
was an actual line of code.legend.title
parameter to control the title of the legend.SCpubr::save_Plot()
SCpubr::do_LigandReceptorPlot()
and SCpubr::do_SankeyPlot()
.enforce_symmetry = TRUE
to have the middle color as grey95
instead of the previous one, which made middle values seem closer to the positive end of the scale.rotate_x_axis_labels
parameter in all functions that made use of it. Now, instead of accepting a logical
, accepts a numeric
: either 0
, 45
or 90
, corresponding to the degrees in which the X axis labels should be rotated. (#5)SCpubr::do_CopyNumberVariantPlot
SCpubr::do_CopyNumberVariantPlot
to also report results for the whole chromosome as well as for each chromosome arm.verbose
argument to SCpubr::do_CopyNumberVariantPlot
to silence the messages when there are not enough genes in the chromosome to perform the analysis.SCpubr::do_DimPlot()
SCpubr::do_DimPlot()
when cell borders are displayed.group.by
and split.by
functionality to SCpubr::do_DimPlot()
. (#4)SCpubr::do_DotPlot()
SCpubr::do_FeaturePlot()
SCpubr::do_FeaturePlot
when setting enforce_symmetry = TRUE
.order
in SCpubr::do_FeaturePlot()
from TRUE
to FALSE
.min.cutoff
and max.cutoff
parameters to SCpubr::do_FeaturePlot()
. This allows to effectively subset the color scale to the values provided. Cells outside the range will be converted to the min or max values provided, respectively. (#2)SCpubr::do_GeyserPlot()
flip
parameter.SCpubr::do_GroupwiseDEPlot()
SCpubr::do_GroupwiseDEPlot
in which the heatmap could not be computed. (#3)SCpubr::do_GroupwiseDEPlot
. (#3)SCpubr::do_LigandReceptorPlot()
(development release)x_labels_angle
to rotate_x_axis_labels
to keep a consistent terminology.SCpubr::do_RidgePlot()
panel.grid.minor
to be displayed in SCpubr::do_Ridgeplot()
.flip
parameter.SCpubr::do_ViolinPlot()
split.by
functionality to SCpubr::do_ViolinPlot()
. (#4, #5)flip
parameter.feature
parameter to features
, to better reflect the multiple feature behavior.Seurat
's share.y.lims
behavior and set it to share.y.lims
parameter. (#5)SCpubr::save_Plot()
SCpubr::do_LigandReceptorPlot()
and SCpubr::do_SankeyPlot()
.SCpubr::save_Plot()
SCpubr::do_LigandReceptorPlot()
and SCpubr::do_SankeyPlot()
.Seurat
do not require this to be installed. This is just for the very side case in which somebody downloads the package just for the SCpubr::do_ColorPalette()
function.individual.titles
, 'individual.subtitlesand
individual.captionsin
SCpubr::do_NebulosaPlot()` as the benefit of such parameters did not surpass the problems the code was causing. The feature might come back in the future, once fully optimized.SCpubr::save_Plot()
function to align with CRAN policies that the package should not write to the file system. The code is still available in the v0.0.0.0.9000 release in Github.SCpubr::do_LigandReceptorPlot()
, SCpubr::do_SankeyPlot()
and SCpubr::do_PseudotimePlot()
to align with CRAN policies and make it possible to publish the package. These functions can still be accessed in the v0.0.0.0.9000 release in Github.SCpubr::do_PseudotimePlot()
for the reason above and because the dependency Matrix.utils
was removed from CRAN on 09-10-2022.SCpubr::save_Plot()
SCpubr::do_LigandReceptorPlot()
and SCpubr::do_SankeyPlot()
.NEWS.md
file to track changes to the package.Add the following code to your website.
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