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.byis 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.scaleand 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().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().sequential.palette and sequential.direction parameters.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.order parameter to reorder the groups based on the median rank.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.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".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.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.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.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.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.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.return_matrix is added, so that the user can use it to compute further analysis or visualizations.order_by_mean to order.order = TRUE now is done based on the median instead of the mean.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.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.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.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.flip and split.by.x_lab and y_lab would not rotate accordingly when using flip = TRUE.groupOnX parameter of geom_quarirandom. This will likely affect users with a lower version.assay to NULL and will default to the default assay in the seurat object.viridis_direction parameter.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.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.label, label.size and label.color parameter to reproduce the same behavior as in Seurat::FeaturePlot().assay to NULL and will default to the default assay in the seurat object.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))enforce_symmetry is set to FALSE, then the color scale turns into a viridis-based one instead of a two-color gradient scale.enforce_symmetry is set to FALSE, then the color scale turns into a viridis-based one instead of a two-color gradient scale.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.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.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.plot_density_contour.raster.dpi to Seurat versions higher or equal to 4.1.0.color.by implementation due to it being very buggy. This will be re-implemented in a future patch.assay = "RNA" or, in fact, any other assay rather than SCT will result in an error.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 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() when cell borders are displayed.group.by and split.by functionality to SCpubr::do_DimPlot(). (#4)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)flip parameter.SCpubr::do_GroupwiseDEPlot in which the heatmap could not be computed. (#3)SCpubr::do_GroupwiseDEPlot. (#3)x_labels_angle to rotate_x_axis_labels to keep a consistent terminology.panel.grid.minor to be displayed in SCpubr::do_Ridgeplot().flip parameter.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.subtitlesandindividual.captionsinSCpubr::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.