Using split.by kills na_cutoff for genes with zero expression (no lightgrey points...)

[CroixJeremy2]

Hello, it is me again,

I have found a small visual annoying bug: when all cells have zero expression for a gene of interest, using split.by kills the na_cutoff, which then does not apply correctly, thus the color scale is not showing lightgrey points as it should. Could you correct it please? If this is expected behaviour somehow, can you provide a solution + add a warning for other users please?

Thanks in advance,
Best regards,

#Required libraries
	library(Seurat)
	library(scCustomize)
	library(SeuratData)
	# SeuratData::InstallData("ifnb")

#Minimal example using ifnb dataset
	#Loading
		data(ifnb)
		ifnb = UpdateSeuratObject(object = ifnb)
		ifnb = Convert_Assay(seurat_object = ifnb, convert_to = "V5")

	#Quick pipeline
		ifnb #normalisation already done, no need to run NormalizeData(ifnb)
		ifnb = FindVariableFeatures(ifnb)
		ifnb = ScaleData(ifnb)
		ifnb = RunPCA(ifnb)
		ifnb = RunUMAP(ifnb, dims = 1:30)

	#Extracting the genes that have zero counts for all cells
		matrix = LayerData(object = ifnb[["RNA"]], layer = "data")
		zero_genes = rownames(matrix)[Matrix::rowSums(matrix) == 0]
		zero_genes
			# "HIST2H2BF"
			# "LHX4"
			# "RP1-191J18.66"
			# "RP11-305L7.1"
			# "NUAK1"
			# "RILPL1"
			# "C22orf15"
			# "SLC1A7"
			# "CTA-363E6.6"

	#Merged UMAP that correctly produces lightgrey points as values are below na_cutoff (as expected)
		FeaturePlot_scCustom(seurat_object = ifnb,
							features = "LHX4")
		# Warning message:
		# All cells have the same value (0) of “LHX4”

	#Split UMAP that incorrectly does NOT produce lightgrey points for values that are below na_cutoff...
		FeaturePlot_scCustom(seurat_object = ifnb,
							split.by = "stim",
							features = "LHX4")
		# Warning messages:
		# 1: All cells have the same value (0) of “LHX4”
		# 2: All cells have the same value (0) of “LHX4”

	#Even setting a tiny na_cutoff does not solve the problem...
		FeaturePlot_scCustom(seurat_object = ifnb,
							split.by = "stim",
							na_cutoff = 1e-300,
							features = "LHX4")

sessionInfo() output

> sessionInfo()
R version 4.6.1 (2026-06-24)
Platform: aarch64-apple-darwin23
Running under: macOS Tahoe 26.5.2

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.6/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.6/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.1

locale:
[1] C.UTF-8/C.UTF-8/C.UTF-8/C/C.UTF-8/C.UTF-8

time zone: Europe/Paris
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] pbmc3k.SeuratData_3.1.4 ifnb.SeuratData_3.0.0   SeuratData_0.2.2.9002  
[4] scCustomize_3.3.1.9004  Seurat_5.5.1            SeuratObject_5.4.0     
[7] sp_2.2-1               

loaded via a namespace (and not attached):
  [1] RColorBrewer_1.1-3     rstudioapi_0.19.0      jsonlite_2.0.0        
  [4] shape_1.4.6.1          magrittr_2.0.5         spatstat.utils_3.2-3  
  [7] ggbeeswarm_0.7.3       farver_2.1.2           GlobalOptions_0.1.4   
 [10] vctrs_0.7.3            ROCR_1.0-12            spatstat.explore_3.8-1
 [13] paletteer_1.7.0        janitor_2.2.1          htmltools_0.5.9       
 [16] forcats_1.0.1          sctransform_0.4.3      parallelly_1.48.0     
 [19] KernSmooth_2.23-26     htmlwidgets_1.6.4      ica_1.0-3             
 [22] plyr_1.8.9             plotly_4.12.0          zoo_1.8-15            
 [25] lubridate_1.9.5        igraph_2.3.3           mime_0.13             
 [28] lifecycle_1.0.5        pkgconfig_2.0.3        Matrix_1.7-5          
 [31] R6_2.6.1               fastmap_1.2.0          fitdistrplus_1.2-6    
 [34] future_1.70.0          shiny_1.14.0           snakecase_0.11.1      
 [37] digest_0.6.39          colorspace_2.1-2       rematch2_2.1.2        
 [40] patchwork_1.3.2        tensor_1.5.1           RSpectra_0.16-2       
 [43] irlba_2.3.7            labeling_0.4.3         progressr_1.0.0       
 [46] spatstat.sparse_3.2-0  timechange_0.4.0       httr_1.4.8            
 [49] polyclip_1.10-7        abind_1.4-8            compiler_4.6.1        
 [52] withr_3.0.3            S7_0.2.2               fastDummies_1.7.6     
 [55] MASS_7.3-65            rappdirs_0.3.4         tools_4.6.1           
 [58] vipor_0.4.7            lmtest_0.9-40          otel_0.2.0            
 [61] beeswarm_0.4.0         httpuv_1.6.17          future.apply_1.20.2   
 [64] goftest_1.2-3          glue_1.8.1             nlme_3.1-169          
 [67] promises_1.5.0         grid_4.6.1             Rtsne_0.17            
 [70] cluster_2.1.8.2        reshape2_1.4.5         generics_0.1.4        
 [73] gtable_0.3.6           spatstat.data_3.1-9    tidyr_1.3.2           
 [76] data.table_1.18.4      spatstat.geom_3.8-1    RcppAnnoy_0.0.23      
 [79] ggrepel_0.9.8          RANN_2.6.2             pillar_1.11.1         
 [82] stringr_1.6.0          spam_2.11-4            RcppHNSW_0.7.0        
 [85] ggprism_1.0.7          later_1.4.8            circlize_0.4.18       
 [88] splines_4.6.1          dplyr_1.2.1            lattice_0.22-9        
 [91] survival_3.8-6         deldir_2.0-4           tidyselect_1.2.1      
 [94] miniUI_0.1.2           pbapply_1.7-4          gridExtra_2.3.1       
 [97] scattermore_1.2        matrixStats_1.5.0      stringi_1.8.7         
[100] lazyeval_0.2.3         codetools_0.2-20       tibble_3.3.1          
[103] cli_3.6.6              uwot_0.2.4             xtable_1.8-8          
[106] reticulate_1.46.0      Rcpp_1.1.2             globals_0.19.1        
[109] spatstat.random_3.5-0  mcprogress_0.1.1       png_0.1-9             
[112] ggrastr_1.0.2          spatstat.univar_3.2-0  parallel_4.6.1        
[115] ggplot2_4.0.3          dotCall64_1.2          listenv_1.0.0         
[118] viridisLite_0.4.3      scales_1.4.0           ggridges_0.5.7        
[121] purrr_1.2.2            crayon_1.5.3           rlang_1.3.0           
[124] cowplot_1.2.0         

[CroixJeremy2]

Workaround/patch by AI... (look for "PATCH" comments). I don't know if the solution/logic is OK or not though:

# Patched FeaturePlot_scCustom with fix for na_cutoff + split.by on all-zero genes ----
# Search [PATCH] to find the two modified blocks.

FeaturePlot_scCustom_MANUAL_UPDATE = function(seurat_object, features, colors_use = viridis_plasma_dark_high,
	na_color = "lightgray", order = TRUE, pt.size = NULL, reduction = NULL,
	na_cutoff = 1e-09, raster = NULL, raster.dpi = c(512, 512),
	split.by = NULL, split_collect = NULL, aspect_ratio = NULL,
	figure_plot = FALSE, num_columns = NULL, layer = "data",
	alpha_exp = NULL, alpha_na_exp = NULL, label = FALSE, label_feature_yaxis = FALSE,
	max.cutoff = NA, min.cutoff = NA, combine = TRUE, ...)
{
	Is_Seurat(seurat_object = seurat_object)
	if (!is.null(x = split.by)) {
		split.by <- Meta_Present(object = seurat_object, meta_col_names = split.by,
			print_msg = FALSE, omit_warn = FALSE)[[1]]
	}
	if (is.null(x = split_collect)) {
		if (length(x = features) == 1) {
			split_collect <- TRUE
		}
		else {
			split_collect <- FALSE
		}
	}
	if (!is.null(x = split_collect)) {
		if (length(x = features) > 1 && isTRUE(x = split_collect)) {
			cli_abort(message = "{.code split_collect} cannot be set to {.field TRUE} if the number of features is greater than 1.")
		}
	}
	all_found_features <- Feature_PreCheck(object = seurat_object,
		features = features)
	if (is.null(x = split.by) && isTRUE(x = label_feature_yaxis)) {
		cli_abort(message = "Setting {.code label_feature_yaxis = TRUE} is only supported when also setting {.code split.by}.")
	}
	if (!is.null(x = split.by)) {
		split.by_length <- length(x = unique(x = seurat_object@meta.data[[split.by]]))
		if (!is.null(x = num_columns) && isTRUE(x = label_feature_yaxis)) {
			cli_warn(message = c("Setting number of columns is not permitted if {.code label_feature_yaxis = TRUE}",
				i = "Number of columns be automatically set to number of levels in `split.by` ({.field {split.by_length}})."))
			num_columns <- split.by_length
		}
		if (is.null(x = num_columns)) {
			num_columns <- split.by_length
		}
		num_rows <- ceiling(split.by_length/num_columns)
		if (num_columns > split.by_length) {
			cli_abort(message = c("The number of columns specified is greater than the number of meta data variables.",
				`*` = "{.val {split.by}} only contains {.field {split.by_length}} variables.",
				i = "Please adjust {.code num_columns} to be less than or equal to {.field {split.by_length}}."))
		}
	}
	if (any(all_found_features %in% colnames(x = seurat_object@meta.data))) {
		cli_warn(message = c("Some of the plotted features are from meta.data slot.",
			`*` = "Please check that {.code na_cutoff} param is being set appropriately for those features."))
	}
	raster <- raster %||% (length(x = Cells(x = seurat_object)) >
		2e+05)
	if (is.null(x = pt.size)) {
		if (!is.null(x = split.by)) {
			cells_by_meta <- data.frame(table(seurat_object@meta.data[,
				split.by]))
			max_cells <- max(cells_by_meta$Freq)
			pt.size <- AutoPointSize_scCustom(data = max_cells,
				raster = raster)
		}
		else {
			cells_total <- nrow(x = seurat_object@meta.data)
			pt.size <- AutoPointSize_scCustom(data = cells_total,
				raster = raster)
		}
	}
	if (is.null(x = na_cutoff)) {
		na_cutoff <- NA
	}
	reduction <- reduction %||% DefaultDimReduc(object = seurat_object)
	seurat_version <- packageVersion("Seurat")
	if (!is.null(x = alpha_exp) && seurat_version < "5") {
		colors_use <- alpha(colors_use, alpha_exp)
	}
	if (!is.null(x = alpha_na_exp) && seurat_version < "5") {
		na_color <- alpha(na_color, alpha_na_exp)
	}
	if (!is.null(x = alpha_na_exp) && seurat_version >= "5") {
		cli_warn(message = "{.code alpha_na_exp} is not currently supported for Seurat v5+")
	}
	if (is.null(x = alpha_exp) && seurat_version >= "5") {
		alpha_exp <- 1
	}
	if (length(x = min.cutoff) > 1 && length(x = min.cutoff) !=
		length(x = all_found_features)) {
		cli_abort(message = "The length of {.code min.cutoff} ({.field {length(x = min.cutoff)}}) must be single value or equal in length to number of features being plotted ({.field {length(x = all_found_features)}}).")
	}
	if (length(x = max.cutoff) > 1 && length(x = max.cutoff) !=
		length(x = all_found_features)) {
		cli_abort(message = "The length of {.code max.cutoff} ({.field {length(x = max.cutoff)}}) must be single value or equal in length to number of features being plotted ({.field {length(x = all_found_features)}}).")
	}
	if (is.null(x = split.by) && isTRUE(x = combine)) {
		if (seurat_version >= "5") {
			plot <- suppressMessages(FeaturePlot(object = seurat_object,
				features = all_found_features, order = order,
				pt.size = pt.size, reduction = reduction, raster = raster,
				split.by = split.by, ncol = num_columns, combine = combine,
				raster.dpi = raster.dpi, label = label, alpha = alpha_exp,
				min.cutoff = min.cutoff, max.cutoff = max.cutoff,
				...) & scale_color_gradientn(colors = colors_use,
				limits = c(na_cutoff, NA), na.value = na_color))
		}
		else {
			plot <- suppressMessages(FeaturePlot(object = seurat_object,
				features = all_found_features, order = order,
				pt.size = pt.size, reduction = reduction, raster = raster,
				split.by = split.by, ncol = num_columns, combine = combine,
				raster.dpi = raster.dpi, label = label, min.cutoff = min.cutoff,
				max.cutoff = max.cutoff, ...) & scale_color_gradientn(colors = colors_use,
				limits = c(na_cutoff, NA), na.value = na_color))
		}
	}
	if (is.null(x = split.by) && isFALSE(x = combine)) {
		if (seurat_version >= "5") {
			plot_list <- suppressMessages(FeaturePlot(object = seurat_object,
				features = all_found_features, order = order,
				pt.size = pt.size, reduction = reduction, raster = raster,
				split.by = split.by, ncol = num_columns, combine = combine,
				raster.dpi = raster.dpi, label = label, alpha = alpha_exp,
				min.cutoff = min.cutoff, max.cutoff = max.cutoff,
				...))
			plot <- lapply(1:length(x = plot_list), function(i) {
				plot_list[[i]] <- suppressMessages(plot_list[[i]] +
					scale_color_gradientn(colors = colors_use,
						limits = c(na_cutoff, NA), na.value = na_color))
			})
		}
		else {
			plot_list <- suppressMessages(FeaturePlot(object = seurat_object,
				features = all_found_features, order = order,
				pt.size = pt.size, reduction = reduction, raster = raster,
				split.by = split.by, ncol = num_columns, combine = combine,
				raster.dpi = raster.dpi, label = label, min.cutoff = min.cutoff,
				max.cutoff = max.cutoff, ...))
			plot <- lapply(1:length(x = plot_list), function(i) {
				plot_list[[i]] <- suppressMessages(plot_list[[i]] +
					scale_color_gradientn(colors = colors_use,
						limits = c(na_cutoff, NA), na.value = na_color))
			})
		}
	}
	if (!is.null(x = split.by) && length(x = all_found_features) ==
		1) {
		feature_data <- FetchData(object = seurat_object, vars = all_found_features,
			layer = layer)
		min.cutoff <- mapply(FUN = function(cutoff, feature) {
			return(ifelse(test = is.na(x = cutoff), yes = min(feature_data[,
				feature]), no = cutoff))
		}, cutoff = min.cutoff, feature = all_found_features)
		max.cutoff <- mapply(FUN = function(cutoff, feature) {
			return(ifelse(test = is.na(x = cutoff), yes = max(feature_data[,
				feature]), no = cutoff))
		}, cutoff = max.cutoff, feature = all_found_features)
		check.lengths <- unique(x = vapply(X = list(all_found_features,
			min.cutoff, max.cutoff), FUN = length, FUN.VALUE = numeric(length = 1)))
		if (length(x = check.lengths) != 1) {
			cli_abort(message = "There must be the same number of minimum and maximum cuttoffs as there are features")
		}
		names(x = min.cutoff) <- names(x = max.cutoff) <- all_found_features
		max_exp_value <- max.cutoff
		min_exp_value <- min.cutoff

		# [PATCH] Guard against inverted scale limits when max expression <= na_cutoff
		# (e.g., all cells have zero expression). Reset upper limit to NA so ggplot2
		# auto-resolves, consistent with the non-split path behaviour.
		if (!is.na(na_cutoff) && max_exp_value <= na_cutoff) {
			cli_warn(message = c(
				"Maximum expression for {.field {all_found_features}} ({.val {max_exp_value}}) is at or below {.code na_cutoff} ({.val {na_cutoff}}).",
				i = "All cells will be colored with {.code na_color} ({.val {na_color}})."
			))
			max_exp_value <- NA
		}
		# [END PATCH]

		if (seurat_version >= "5") {
			plot <- suppressMessages(FeaturePlot(object = seurat_object,
				features = all_found_features, order = order,
				pt.size = pt.size, reduction = reduction, raster = raster,
				split.by = split.by, raster.dpi = raster.dpi,
				label = label, alpha = alpha_exp, , min.cutoff = min.cutoff,
				max.cutoff = max.cutoff, ...) & scale_color_gradientn(colors = colors_use,
				limits = c(na_cutoff, max_exp_value), na.value = na_color,
				name = all_found_features)) & RestoreLegend() &
				theme(axis.title.y.right = element_blank())
		}
		else {
			plot <- suppressMessages(FeaturePlot(object = seurat_object,
				features = all_found_features, order = order,
				pt.size = pt.size, reduction = reduction, raster = raster,
				split.by = split.by, raster.dpi = raster.dpi,
				label = label, min.cutoff = min.cutoff, max.cutoff = max.cutoff,
				...) & scale_color_gradientn(colors = colors_use,
				limits = c(na_cutoff, max_exp_value), na.value = na_color,
				name = all_found_features)) & RestoreLegend() &
				theme(axis.title.y.right = element_blank())
		}
		if (isTRUE(x = label_feature_yaxis)) {
			plot <- plot + plot_layout(nrow = num_rows, ncol = num_columns)
			plot <- plot & theme(legend.title = element_blank())
			plot <- suppressMessages(plot + scale_y_continuous(sec.axis = dup_axis(name = all_found_features))) +
				No_Right()
		}
		else {
			if (isTRUE(x = split_collect)) {
				if (hasArg("keep.scale")) {
					cli_abort(message = "The parameter {.code keep.scale} cannot be set different from default if {.code split_collect - TRUE}.")
				}
				plot <- plot + plot_layout(nrow = num_rows, ncol = num_columns,
					guides = "collect")
			}
			else {
				plot <- plot + plot_layout(nrow = num_rows, ncol = num_columns)
			}
		}
	}
	if (!is.null(x = split.by) && length(x = all_found_features) >
		1) {
		if (length(x = min.cutoff) == 1) {
			min.cutoff <- rep(x = min.cutoff, length(x = all_found_features))
		}
		if (length(x = max.cutoff) == 1) {
			max.cutoff <- rep(x = max.cutoff, length(x = all_found_features))
		}
		plot_list <- lapply(1:length(x = all_found_features),
			function(i) {
				feature_data <- FetchData(object = seurat_object,
					vars = all_found_features[i], layer = layer)
				min.cutoff <- mapply(FUN = function(cutoff, feature) {
					return(ifelse(test = is.na(x = cutoff), yes = min(feature_data[,
						feature]), no = cutoff))
				}, cutoff = min.cutoff[i], feature = all_found_features[i])
				max.cutoff <- mapply(FUN = function(cutoff, feature) {
					return(ifelse(test = is.na(x = cutoff), yes = max(feature_data[,
						feature]), no = cutoff))
				}, cutoff = max.cutoff[i], feature = all_found_features[i])
				check.lengths <- unique(x = vapply(X = list(all_found_features[i],
					min.cutoff, max.cutoff), FUN = length, FUN.VALUE = numeric(length = 1)))
				if (length(x = check.lengths) != 1) {
					cli_abort(message = "There must be the same number of minimum and maximum cuttoffs as there are features")
				}
				names(x = min.cutoff) <- names(x = max.cutoff) <- all_found_features[i]
				max_exp_value <- max.cutoff
				min_exp_value <- min.cutoff

				# [PATCH] Guard against inverted scale limits when max expression <= na_cutoff
				# (e.g., all cells have zero expression). Reset upper limit to NA so ggplot2
				# auto-resolves, consistent with the non-split path behaviour.
				if (!is.na(na_cutoff) && max_exp_value <= na_cutoff) {
					cli_warn(message = c(
						"Maximum expression for {.field {all_found_features[i]}} ({.val {max_exp_value}}) is at or below {.code na_cutoff} ({.val {na_cutoff}}).",
						i = "All cells will be colored with {.code na_color} ({.val {na_color}})."
					))
					max_exp_value <- NA
				}
				# [END PATCH]

				if (seurat_version >= "5") {
					single_plot <- suppressMessages(FeaturePlot(object = seurat_object,
						features = all_found_features[i], order = order,
						pt.size = pt.size, reduction = reduction,
						raster = raster, split.by = split.by, raster.dpi = raster.dpi,
						label = label, alpha = alpha_exp, min.cutoff = min.cutoff,
						max.cutoff = max.cutoff, ...) & scale_color_gradientn(colors = colors_use,
						limits = c(na_cutoff, max_exp_value), na.value = na_color,
						name = all_found_features[i])) & RestoreLegend() &
						theme(axis.title.y.right = element_blank())
				}
				else {
					single_plot <- suppressMessages(FeaturePlot(object = seurat_object,
						features = all_found_features[i], order = order,
						pt.size = pt.size, reduction = reduction,
						raster = raster, split.by = split.by, raster.dpi = raster.dpi,
						label = label, min.cutoff = min.cutoff, max.cutoff = max.cutoff,
						...) & scale_color_gradientn(colors = colors_use,
						limits = c(na_cutoff, max_exp_value), na.value = na_color,
						name = features[i])) & RestoreLegend() &
						theme(axis.title.y.right = element_blank())
				}
				if (isTRUE(x = label_feature_yaxis)) {
					single_plot <- single_plot + plot_layout(nrow = num_rows,
						ncol = num_columns)
					single_plot <- single_plot & theme(legend.title = element_blank())
					single_plot <- suppressMessages(single_plot +
						scale_y_continuous(sec.axis = dup_axis(name = all_found_features[i]))) +
						No_Right()
				}
				else {
					single_plot <- single_plot + plot_layout(nrow = num_rows,
						ncol = num_columns)
				}
			})
		plot <- wrap_plots(plot_list) + plot_layout(ncol = 1)
	}
	if (getOption(x = "scCustomize_warn_na_cutoff", default = TRUE) &&
		!is.na(x = na_cutoff) && na_cutoff == 1e-09) {
		cli_inform(message = c("", "NOTE: {.field FeaturePlot_scCustom} uses a specified {.code na_cutoff} when plotting to",
			"color cells with no expression as background color separate from color scale.",
			"Please ensure {.code na_cutoff} value is appropriate for feature being plotted.",
			"Default setting is appropriate for use when plotting from 'RNA' assay.\n",
			"When {.code na_cutoff} not appropriate (e.g., module scores) set to NULL to \n",
			"plot all cells in gradient color palette.", "",
			"-----This message will be shown once per session.-----"))
		options(scCustomize_warn_na_cutoff = FALSE)
	}
	if (getOption(x = "scCustomize_warn_zero_na_cutoff", default = TRUE) &&
		!is.na(x = na_cutoff) && na_cutoff == 0) {
		cli_inform(message = c("", "NOTE: Specified {.code na_cutoff} is set to {.field zero (0)}. This means that only cells/nuclei",
			"with expression less than zero will be plotted with {.code na_color}: {.val {na_color}}.",
			"To plot cells with expression values of zero using {.code na_color} leave",
			"default {.code na_cutoff} value. If you want to plot full spectrum without",
			"{.code na_cutoff} (e.g., for module scores) then set {.code na_cutoff = NULL`}.",
			"", "-----This message will be shown once per session.-----"))
		options(scCustomize_warn_na_cutoff = FALSE)
	}
	if (!is.null(x = aspect_ratio)) {
		if (!is.numeric(x = aspect_ratio)) {
			cli_abort(message = "{.code aspect_ratio} must be a {.field numeric} value.")
		}
		plot <- plot & theme(aspect.ratio = aspect_ratio)
	}
	if (isTRUE(x = figure_plot)) {
		if (length(x = all_found_features) == 1) {
			plot <- Figure_Plot(plot = plot)
		}
		else {
			plot_list <- lapply(1:length(x = all_found_features),
				function(j) {
					fig_plot <- Figure_Plot(plot = plot[[j]])
				})
			plot <- wrap_plots(plot_list, ncol = num_columns)
		}
	}
	return(plot)
}

# [PATCH] Bind the function to scCustomize's namespace so it can access
# internal (non-exported) helpers: Is_Seurat, Meta_Present, Feature_PreCheck,
# AutoPointSize_scCustom, Figure_Plot, No_Right, etc.
environment(FeaturePlot_scCustom_MANUAL_UPDATE) = asNamespace("scCustomize")
# [END PATCH]

[samuel-marsh]

Hi @CroixJeremy2,

Sorry for delay on these issues. New position has kept me busy at work. Thanks for posting code and issue. I’ll take look and hope to resolve these by end of the week.

Thanks!
Sam