updates

# Generated by roxygen2: do not edit by hand

export(Install.example)

export(add_sliding_windows)

export(add_track)

export(cell_order)

export(change_strip_background)

export(get_segment)

export(mk_color_table)

export(mk_marker_ct)

export(modified_coverageplot)

export(modified_dimplot)

export(modified_dotplot)

export(order_gene_down)

export(order_gene_up)

export(plot_circlize)

#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

# Functions

#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

#' Modified CoveragePlot

#'

#' This function is a modified version of the CoveragePlot in Signac that allows gene name input and group splitting

#'

#' @param sig_obj A complete Signac object

#' @param gene Gene name

#' @param slide_windows_up Upper range of the slide window

#' @param slide_windows_down Lower range of the slide window

#' @param split_by Group ID in metadata to split peaks

#' @return A ggplot object

#' @export

modified_coverageplot <- function(

  sig_obj, 

  gene, 

  slide_windows_up, 

  slide_windows_down,

  split_by

){

  celltypes<-levels(sig_obj)

  DefaultAssay(sig_obj)<-'peaks'

  sig_obj@meta.data$disease<-sig_obj@meta.data[,split_by]

  sig_obj@meta.data$celltype<-sig_obj@active.ident

  sig_obj@meta.data$id2<-paste(sig_obj@meta.data$celltype,sig_obj@meta.data$disease,  sep = "_")

  sig_obj<- SetIdent(sig_obj, value = 'id2')

  p2 <- Signac::CoveragePlot(

    object = sig_obj,

    region = gene,

    annotation = T,

    peaks = T, 

    extend.upstream = slide_windows_up,

    extend.downstream = slide_windows_down

  )

  gene.ranges <- genes(EnsDb.Hsapiens.v86)

  seqlevelsStyle(gene.ranges) <- 'UCSC'

  gene.ranges <- keepStandardChromosomes(gene.ranges, pruning.mode = 'coarse')

  region2 <- GRangesToString(subset(gene.ranges, symbol==gene))

  if(region2=='--') {

    next

  }

  if(length(region2)>1){

    region2<-region2[1]

  }

  region2<-add_sliding_windows(region = region2, up_stream = slide_windows_up, down_stream = slide_windows_down)

  xlabel<-p2$patches$plots[1][[1]]$labels$x

  ylabel<-p2$patches$plots[1][[1]]$labels$y

  data_plot<-p2$patches$plots[1][[1]]$data

  data_plot$celltype<-gsub("_[^_]*$", "", data_plot$group )

  data_plot$disease<-gsub(".*_", "", data_plot$group )

  data_plot$celltype <- factor(data_plot$celltype, levels = celltypes)

  a1<-Signac:::PeakPlot(sig_obj,region = region2)

  a2<-p2$patches$plots[2][[1]]

  group_id<-names(table(data_plot$disease))

  a3 <- ggplot(

    data = data_plot[data_plot$disease==group_id[1],],

    mapping = aes(x = position, y = coverage, fill = celltype)

  ) +

    geom_area(stat = "identity") +

    geom_hline(yintercept = 0, size = 0.1) +

    xlab("")+ylab(as_string(ylabel))+ggtitle(group_id[1])+

    theme_browser(legend = FALSE) +

    facet_grid(celltype ~.)+

    theme(

      panel.spacing.y = unit(x = 0, units = "line"),

      plot.title = element_text(size = 14,hjust = 0.5, face = 'bold'),

      strip.text.y = element_text(angle = 0),

      axis.ticks.x = element_blank(),

      axis.text.x = element_blank(),

      axis.line.x = element_blank())

  a4 <- ggplot(

    data = data_plot[data_plot$disease==group_id[2],],

    mapping = aes(x = position, y = coverage, fill = celltype)

  ) +

    geom_area(stat = "identity") +

    geom_hline(yintercept = 0, size = 0.1) +

    xlab("")+

    ylab("")+

    ggtitle(group_id[2])+

    theme_browser(legend = FALSE) +

    facet_grid(celltype ~.)+

    theme(

      plot.title = element_text(size = 14,hjust = 0.5, face = 'bold'),

      strip.text.y = element_blank(),

      axis.ticks = element_blank(),

      axis.text = element_blank(),

      axis.line = element_blank())

  a5 <- a2 + ylab("")

  a6 <- a1 + ylab("")

  p3 <- a3 + a2 + a1  + plot_layout(heights = c(6,1,1))

  p4 <- a4 + a5 + a6  + plot_layout(heights = c(6,1,1))

  plot_grid(p3, p4, ncol = 2, rel_widths = c(2.4, 2))

}

#' Add extended windows for coverage plot

#'

#' This function is to add an extended window for ploting

#'

#' @param region Gene region for plotting

#' @param up_stream Upper range of the slide window

#' @param down_stream Lower range of the slide window

#' @return Gene range for plot

#' @export

add_sliding_windows <- function(

  region,

  up_stream, 

  down_stream

){

  reg_list<-strsplit(region, split = "-")

  reg_list<-as.character(unlist(reg_list))

  new_reg<-paste(reg_list[1], as.integer(reg_list[2])-down_stream, as.integer(reg_list[3])+up_stream, sep = "-")

  new_reg

}

 No newline at end of file

#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

# Functions

#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

#' Modified DotPlot

#'

#' This function is a modified version of the DotPlot function in Seurat

#'

#' @param seu_obj A complete Seurat object

#' @param features A vector of gene names.

#' @return A ggplot object

#' @export

modified_dotplot <- function(

  seu_obj, 

  features, 

  col_palette = NULL,

  scale.by='radius'

){

  levels(seu_obj) <- rev(levels(seu_obj))

  dataplot<-DotPlot(seu_obj, features = features)

  dataplot<-dataplot$data

  dataplot$avg.exp<-dataplot$avg.exp.scaled

  colnames(dataplot)[1:2]<-c('Avg.Exp', 'Pct.Exp')

  if(is.null(col_palette)){

    col_palette = colorRampPalette(c('grey80','lemonchiffon1','indianred1','darkred'))(255)

  }

  scale.func <- switch(

    EXPR = scale.by,

    'size' = scale_size,

    'radius' = scale_radius,

    stop("'scale.by' must be either 'size' or 'radius'")

  )

  dotplot<-ggplot(dataplot, aes(x = features.plot, y = id, fill=Avg.Exp)) + 

    geom_tile(fill="white", color="white") +

    geom_point(aes( size =Pct.Exp), shape=21, color='grey80')  +  

    scale_fill_gradientn(colours  =  col_palette)+

    theme(panel.background = element_rect(fill = "white", colour = "black"),

          axis.line = element_blank(),axis.text.x = element_text(angle = 45, hjust = 1), 

          legend.key = element_rect(colour = NA, fill = NA),

          axis.text = element_text(size = 12),axis.title=element_text(size=8),legend.text=element_text(size=8), 

          legend.title = element_text(size = 10),legend.position="right", legend.margin=margin())+ylab("")+xlab("")+

    guides(size = guide_legend(override.aes = list(color='black')))

  if(max(dataplot$Pct.Exp)>=20) {

    dotplot + scale_size(range = c(0, 10))

  } else {

    dotplot + scale.func(range = c(0, 10), limits = c(0, 20))

  }

  dotplot

}

#' Modified DimPlot

#'

#' This function is a modified version of the DimPlot function in Seurat

#'

#' @param seu_obj A complete Seurat object

#' @param colors Colors to label the clusters

#' @param pt.size Size of the data points

#' @param label.box Whether or not to label the cell type name

#' @param label.size Font size of the labels

#' @param do.reple Whether or not to repel the cluster annotation

#' @param title Main title of the plot

#' @return A ggplot object

#' @export

modified_dimplot <- function(

  seu_obj,

  colors = NULL,

  pt.size = 0.5,

  label.box = T,

  label.size = 6,

  do.repel=F,

  title = "UMAP plot"

){

  if(is.null(colors)){

    colors = scales::hue_pal()(length(levels(seu_obj)))

  }

  x0<-min(seu_obj@reductions$umap@cell.embeddings[,1])

  x1<-x0+(max(seu_obj@reductions$umap@cell.embeddings[,1])-min(seu_obj@reductions$umap@cell.embeddings[,1]))/8

  y0<-min(seu_obj@reductions$umap@cell.embeddings[,2])

  y1<-y0+(max(seu_obj@reductions$umap@cell.embeddings[,2])-min(seu_obj@reductions$umap@cell.embeddings[,2]))/8

  DimPlot(seu_obj, label = T, cols = colors,label.box = label.box, 

          label.size = label.size, pt.size = pt.size, raster = F, repel = do.repel)+NoLegend()+NoAxes()+

    geom_segment(aes(x=x0, xend = x1 , y=y0, yend = y0), size=0.8,

                 arrow = arrow(length = unit(0.2,"cm"))) +

    geom_segment(aes(x=x0, xend = x0 , y=y0, yend = y1), size=0.8,

                 arrow = arrow(length = unit(0.2,"cm"))) +

    xlab("UMAP_1")+theme(axis.title.x = element_text(hjust = 0.05, size = 12))+

    ylab('UMAP_2')+theme(axis.title.y = element_text(hjust = 0.05, angle = 90, size = 12))+

    ggtitle(title)+theme(plot.title = element_text(hjust = 0.5))

}

# plot1cell: a package for advanced single cell data visualization

This package allows users to visualize the single cell data on the R objects or output files generated by the popular tools such as Seurat. It is currently under active development. 

This package allows users to visualize the single cell data on the R object or output files generated by Seurat. It is currently under active development. 

## Installation

plot1cell R package can be easily installed from Github using devtools. Please make sure you have installed <a href="https://satijalab.org/seurat/">Seurat 4.0</a>, <a href="https://github.com/jokergoo/circlize">circlize</a> and <a href="https://github.com/jokergoo/ComplexHeatmap">ComplexHeatmap</a> packages.

% Generated by roxygen2: do not edit by hand

% Please edit documentation in R/modified_coverageplot.R

\name{add_sliding_windows}

\alias{add_sliding_windows}

\title{Add extended windows for coverage plot}

\usage{

add_sliding_windows(region, up_stream, down_stream)

}

\arguments{

\item{region}{Gene region for plotting}

\item{up_stream}{Upper range of the slide window}

\item{down_stream}{Lower range of the slide window}

}

\value{

Gene range for plot

}

\description{

This function is to add an extended window for ploting

}