bug fixes

export(complex_dotplot_single)

export(complex_featureplot)

export(complex_heatmap_group)

export(complex_vlnplot_multiple)

export(complex_vlnplot_single)

export(convert_geneid)

export(creat_cellphonedb_file)

if(is.null(label1)){

  label1=rownames(data_plot)

}

ComplexHeatmap::ht_opt$message = FALSE

ht_opt$message = FALSE

ht<- Heatmap(data_plot,name = "mat", cluster_rows = F, cluster_columns = F, 

             column_title = NULL,col = col_fun, row_title = NULL,

             cluster_row_slices = FALSE, cluster_column_slices = FALSE,

  }

}

#' Violin plot for multiple genes across groups

#'

#' This function generates violin plot(s) to compare the expression of multiple genes across 

#' different groups or cell types. It is designed for visualizing a complicated scenario: 

#' Gene expression of multiple genes on multiple cell types across groups.

#'

#' @param seu_obj A complete Seurat object

#' @param features Gene name. Only one gene is allowed.

#' @param celltypes Cell types of interest. By default, all cell types are included.

#' @param group Only one groupID is allowed.

#' @param add.dot Whether or not to add points on the violins.

#' @param font.size Font size for the labels.

#' @param pt.size Point size for the data points on the violin

#' @return A ggplot object

#' @export

complex_vlnplot_multiple <- function(

  seu_obj,

  features,

  celltypes=NULL,

  group,

  add.dot = T,

  font.size=14,

  pt.size=0.1

){

  if(length(features)<2){

    stop("At least two genes are required. For single gene violin plot, please use complex_vlnplot_single instead.")

  }

  if(length(group)>1){

    stop("Use violin plot to show multiple genes in multiple group categories across multiple cell types will look too messy. Please use one group ID only.")

  }

  if(is.null(celltypes)){

    celltypes = levels(seu_obj)

  } 

  gene_count<-extract_gene_count(seu_obj=seu_obj, features = features, cell.types = celltypes, meta.groups = group)

  if (is.null(levels(seu_obj@meta.data[,group]))){

    seu_obj@meta.data[,group] <-factor(seu_obj@meta.data[,group], levels = names(table(seu_obj@meta.data[,group])))

  }

  group_level<-levels(seu_obj@meta.data[,group])

  gene_count[,group]<-factor(gene_count[,group],levels = group_level)

  for(i in 1:length(features)){

    max_exp<-max(gene_count[,features[i]])

    set.seed(seed = 42)

    noise <- rnorm(n = length(x = gene_count[,features[i]])) / 100000

    gene_count[, features[i]]<-gene_count[,features[i]]+noise

  }

  gene_count$Cell<-rownames(gene_count)

  gene_count <- reshape2::melt(gene_count, id.vars = c("Cell","celltype",group), measure.vars = features,

                               variable.name = "Genes", value.name = "Expr")

  gene_count[, group]<-factor(gene_count[, group], levels = group_level)

  gene_count[, "celltype"]<-factor(gene_count[, "celltype"], levels = celltypes)

  ##The plot is modified from https://github.com/ycl6/StackedVlnPlot

  p<-ggplot(gene_count, aes_string(group, "Expr", fill = group)) +

    geom_violin(scale = 'width', adjust = 1, trim = TRUE, size=0.3, alpha=0.5, color="pink") +

    scale_y_continuous(expand = c(0, 0), position="right", labels = function(x)

      c(rep(x = "", times = length(x)-2), x[length(x) - 1], "")) +

    facet_grid(rows = vars(Genes), cols = vars(celltype),scales = "free", switch = "y") +

    theme_cowplot(font_size = 12) +

    theme(legend.position = "none", panel.spacing = unit(0, "lines"),

          plot.title = element_text(hjust = 0.5),

          panel.background = element_rect(fill = NA, color = "black"),

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

          strip.background = element_blank(),

          strip.text = element_text(face = "bold"),

          strip.text.y.left = element_text(angle = 0)) +

    xlab("") + ylab("")

  if(add.dot){

    p = p + geom_quasirandom(size=pt.size, alpha=0.2)

  }

  p

}

% Generated by roxygen2: do not edit by hand

% Please edit documentation in R/plot_violin.R

\name{complex_vlnplot_multiple}

\alias{complex_vlnplot_multiple}

\title{Violin plot for multiple genes across groups}

\usage{

complex_vlnplot_multiple(

  seu_obj,

  features,

  celltypes = NULL,

  group,

  add.dot = T,

  font.size = 14,

  pt.size = 0.1

)

}

\arguments{

\item{seu_obj}{A complete Seurat object}

\item{features}{Gene name. Only one gene is allowed.}

\item{celltypes}{Cell types of interest. By default, all cell types are included.}

\item{group}{Only one groupID is allowed.}

\item{add.dot}{Whether or not to add points on the violins.}

\item{font.size}{Font size for the labels.}

\item{pt.size}{Point size for the data points on the violin}

}

\value{

A ggplot object

}

\description{

This function generates violin plot(s) to compare the expression of multiple genes across

different groups or cell types. It is designed for visualizing a complicated scenario:

Gene expression of multiple genes on multiple cell types across groups.

}