R/p06_profile_plot_list_functions.R
In lakhanp1/chipmine: Analyze ChIP-seq Data
Defines functions
get_expression_heatmap_list
get_profile_plot_list
multi_profile_plots
Documented in
get_expression_heatmap_list
get_profile_plot_list
multi_profile_plots
##################################################################################
## function to get a heatmap list of provided TF, polII samples to be used directly for plotting
#' \code{EnrichedHeatmap} plots and \code{ComplexHeatmaps} for multiple samples
#'
#' This method generates profile heatmaps for multiple samples. Optionally, if the sample list
#' has any polII samples, it also generate a heatmap for the polII expression values.
#'
#' @param exptInfo experiment info as data frame with information like sampleID, type, path etc
#' @param genesToPlot A vector of gene IDs which are to be plotted
#' @param clusters Dataframe with cluster information. Two columns must be present in this
#' dataframe: 'cluster', 'geneId'. Default: NULL
#' @param drawClusterAn Logical: Whether to add row annotation heatmap to heatmap list. Default: TRUE
#' @param clusterColor cluster annotation color information. Default: NULL
#' @param clustOrd A character vector of cluster order in the plot. If not provided,
#' clusters are arranged as per character sort order
#' @param profileColors a named list of color objects for each of the sample. Color for profile
#' heatmap should be generated by colorRamp2
#' @param matSource Method by which profile matrix was generated. One of \emph{deeptools, miao,
#' normalizedmatrix}. Default: normalizedmatrix
#' @param targetType One of "region", "point". If targetType is "region", target is used to decide
#' the number of bins over region. Otherwise, for "point", a signle point matrix is expected where
#' the region is extracted around single point. Default: region
#' @param targetName Name to be used for target. Eg: "gene", "TSS", "TES", "summit" etc. default: gene
#' @param matBins A vector with four elements representing the column counts for up, body,
#' down regions and binSize for the profile matrix. Default: \code{c(200, 200, 100, 10)}
#' @param ylimFraction A named list with intensity scores to use as ylimit for top annotation.
#' If the value is single number, it has to be floating point number to extract the quantile and use
#' limit \code{[0, quantile(x)]}. If the value is numeric vector of length 2, the two numbers are used as lower
#' and upper limits for ylimit of top annotation. Default: NULL.
#' @param plotExpression Binry: whether to plot polII expression heatmap or not. Default: FALSE
#' @param expressionData an dataframe which has info: clustering, polII expression, TF binding
#' status for each gene etc. Default: NULL
#' @param keep Same as \code{EnrichedHeatmap::normalizeToMatrix}. First value is used as lower quantile
#' and any value in profile matrix less than lower quantile is set to lower quantile. Second value is
#' used as upper quantile and any value greater than upper quantile is set to upper quantile.
#' Default: \code{c(0, 1)}
#' @param expressionColor color object for polII expression heatmap
#' @param rasterize Binary: whether to rasterize the profile heatmap or not. By default this is set as TRUE
#' for multiple profile plots.
#' @param rasterQual Raster quality. This is the \code{raster_quality} argument \code{Heatmap} function. in Default: 5
#' @param ... Other arguments for EnrichedHeatmap function
#'
#' @return A list object with following elements:
#' \itemize{
#' \item heatmapList: a heatmap list object which has profile heatmaps and optionally expression heatmaps
#' \item profileHeatmaps: a named list of profile heatmaps generated by \code{EnrichedHeatmap}
#' \item expressionHeatmaps: a named list of polII signal heatmaps
#' \item plotGaps: a vector with required gaps between heatmaps while generating multiprofile plots
#' \item profileColors: a named list object with color scale used for each profile heatmap
#' \item expressionColor: a named list object with color scale used for each expression heatmap
#' }
#'
#' @export
#'
#' @examples NA
multi_profile_plots <- function(exptInfo,
genesToPlot,
clusters = NULL,
drawClusterAn = TRUE,
clusterColor = NULL,
clustOrd = NULL,
profileColors = NULL,
matSource = "normalizedmatrix",
targetType = "region",
targetName = "gene",
matBins = c(200, 200, 100, 10),
ylimFraction = NULL,
plotExpression = FALSE,
expressionData = NULL,
expressionColor = NULL,
keep = c(0, 1),
rasterize = TRUE,
rasterQual = 5,
...){
cat("Generating profile heatmaps...\n")
## profile heatmap list for all samples except first
profileList <- get_profile_plot_list(exptInfo = exptInfo,
cluster = clusters,
clusterColor = clusterColor,
clustOrd = clustOrd,
geneList = genesToPlot,
colorList = profileColors,
matrixSource = matSource,
matrixBins = matBins,
targetType = targetType,
targetName = targetName,
ylimFraction = ylimFraction,
keep = keep,
rasterPar = list(use = rasterize, qual = rasterQual),
...)
# cat("Done!!!\n")
expHtList <- list()
expHtList[["polII_color"]] <- expressionColor
if(isTRUE(plotExpression)){
cat("Generating expression heatmaps...\n")
## expression heatmap list
expHtList <- get_expression_heatmap_list(expDf = expressionData,
exptInfo = exptInfo,
genes = genesToPlot,
htColor = expressionColor)
# cat("Done!!!\n")
}
cat("Generating heatmap list object...\n")
## build the heatmap list for plotting
plotGaps <- numeric()
htList <- NULL
if(isTRUE(drawClusterAn)){
htList <- profileList[[ exptInfo$sampleId[1] ]][[ "rowGroupHt" ]]
plotGaps <- c(2)
}
profileColorList <- list()
for(i in 1:nrow(exptInfo)){
sampleID <- exptInfo$sampleId[i]
## add plot elements to the heatmap list
if(exptInfo$IP_tag[i] == "polII"){
## polII expression + profile
if(isTRUE(plotExpression)){
htList <- htList + expHtList[[sampleID]] + profileList[[sampleID]][["heatmap"]]
plotGaps <- append(plotGaps, c(2, 10))
} else{
## only polII profile
htList <- htList + profileList[[sampleID]][["heatmap"]]
plotGaps <- append(plotGaps, 10)
}
} else{
## TF profile
htList <- htList + profileList[[sampleID]][["heatmap"]]
plotGaps <- append(plotGaps, 10)
}
## add profile colors to profileColorList
profileColorList[[sampleID]] <- profileList[[sampleID]][["profileColor"]]
}
plotGaps <- head(plotGaps, -1)
returnList <- list(
"heatmapList" = htList,
"profileHeatmaps" = profileList,
"plotGaps" = plotGaps,
"profileColors" = profileColorList,
"expressionColor" = expHtList$polII_color
)
if(isTRUE(plotExpression)){
returnList[["expressionHeatmaps"]] <- expHtList
}
return(returnList)
}
##################################################################################
##################################################################################
## function to get the profile plots in list() using EnrichedHeatmap package
#' Multiple Enriched Heatmaps as list
#'
#' @param exptInfo experiment info as data frame with information like sampleID, type,
#' path etc
#' @param cluster Dataframe with cluster information. Two columns must be present
#' in this dataframe: 'cluster', 'geneId'. Default: NULL
#' @param clusterColor cluster annotation color information. Default: NULL
#' @param clustOrd A character vector of cluster order in the plot. If not provided,
#' clusters are arranged as per character sort order
#' @param geneList A vector of gene IDs which are to be plotted
#' @param colorList a named list of color objects for each of the sample. Color for
#' profile heatmap should be generated by colorRamp2
#' @param matrixSource Method by which profile matrix was generated. One of \emph{deeptools, miao,
#' normalizedmatrix}. Default: normalizedmatrix
#' @param matrixBins A numeric vector with four elements representing the column
#' counts for up, body, down regions and binSize for the profile matrix.
#' Default: \code{c(200, 200, 100, 10)}
#' @param targetType One of "region", "point". If targetType is "region", target is used to decide
#' the number of bins over region. Otherwise, for "point", a signle point matrix is expected where
#' the region is extracted around single point. Default: region
#' @param targetName Name to be used for target. Eg: "gene", "TSS", "TES", "summit" etc. default: gene
#' @param ylimFraction A named list with intensity scores to use as ylimit for top annotation.
#' If the value is single number, it has to be floating point number to extract the quantile and use
#' limit \code{[0, quantile(x)]}. If the value is numeric vector of length 2, the two numbers are used as lower
#' and upper limits for ylimit of top annotation. Default: NULL.
#' @param keep Same as \code{EnrichedHeatmap::normalizeToMatrix}. First value is used as lower quantile
#' and any value in profile matrix less than lower quantile is set to lower quantile. Second value is
#' used as upper quantile and any value greater than upper quantile is set to upper quantile.
#' Default: \code{c(0, 1)}
#' @param rasterPar rasterization parameters as list() with two elements: use, qual. Default:
#' \code{list(use = TRUE, qual = 5)}. \code{rasterPar$use} is used for \code{use_raster} argument and
#' \code{rasterPar$qual} is used for \code{raster_quality} argument of \code{Heatmap} function.
#' @param ... Other arguments for \code{EnrichedHeatmap} function
#'
#' @return A named list of Enriched Heatmap objects
#' @export
#'
#' @examples NA
get_profile_plot_list <- function(exptInfo,
cluster = NULL,
clusterColor = NULL,
clustOrd = NULL,
geneList,
colorList = NULL,
matrixSource = "normalizedmatrix",
matrixBins = c(200, 200, 100, 10),
targetType = "region",
targetName = "gene",
ylimFraction = NULL,
keep = c(0, 1),
rasterPar = list(use = TRUE, qual = 5),
...){
allPlots <- list()
## generate plot for each sample
for(i in 1:nrow(exptInfo)){
sampleName <- exptInfo$sampleId[i]
cat("Generating profile heatmap for:", sampleName, "...\n")
mat <- import_profile_from_file(file = exptInfo$matFile[i],
source = matrixSource,
signalName = sampleName,
selectGenes = geneList,
up = matrixBins[1],
target = matrixBins[2],
down = matrixBins[3],
binSize = matrixBins[4],
keep = keep,
targetType = targetType,
targetName = targetName)
qtDistr <- quantile(mat, c(seq(0, 0.9, by = 0.1), 0.95, 0.99, 0.992, 0.995, 0.999, 1), na.rm = T)
print(qtDistr)
## color: generate if colorList = NULL
tfCol <- colorRamp2(quantile(mat, c(0.50, 0.99), na.rm = T), c("white", "red"))
polIICol <- colorRamp2(quantile(mat, c(0.01, 0.5, 0.995), na.rm = T), c("blue", "white", "red"))
colFun <- tfCol
if(exptInfo$IP_tag[i] == "polII"){
colFun <- polIICol
}
## if the colors are provided with colorList argument, use those colors instead
if(!is.null(colorList[[sampleName]])){
colFun <- colorList[[sampleName]]
} else{
cat("Profile color for sample", sampleName, "not provided. Using internal default quantiles to generate color\n")
}
## build the profile heatmap
profile2 <- profile_heatmap(profileMat = mat,
signalName = exptInfo$profileName[i],
columnTitle = exptInfo$sampleName[i],
geneGroups = cluster,
profileColor = colFun,
clusterColor = clusterColor,
clusterOrder = clustOrd,
ylimFraction = ylimFraction[[sampleName]],
rasterPar = rasterPar,
...)
## append to the plot list
allPlots[[ sampleName ]] <- profile2
}
return(allPlots)
}
##################################################################################
##################################################################################
## get the pol-II expression heatmap in list() of class ComplexHeatmap for many samples
#' Multiple PolII expression heatmaps as list
#'
#' @param expDf a dataframe with PolII expression columns
#' @param exptInfo experiment info as data frame with information like sampleID, type, path etc
#' @param htColor heatmap color generated by \code{ColorRamp2}
#' @param genes A vector of gene IDs which are to be plotted
#'
#' @return A named list object with multiple Heatmaps
#' @export
#'
#' @examples NA
get_expression_heatmap_list <- function(expDf,
exptInfo,
genes,
htColor = NULL){
polII_ids <- exptInfo$sampleId[which(exptInfo$IP_tag == "polII")]
polII_expIds <- paste("is_expressed.", polII_ids, sep = "")
## select the gene of interst for plotting
geneSet <- data.frame(geneId = unique(genes), stringsAsFactors = F) %>%
dplyr::left_join(y = expDf, by = c("geneId" = "geneId"))
## clustering polII expression data
rownames(geneSet) <- geneSet$geneId
polII_mat <- as.matrix(geneSet[polII_ids])
polII_log2_mat <- log2(polII_mat + 1)
## polII Heatmap
quantile(polII_log2_mat, c(seq(0, 0.9, by = 0.1), 0.95, 0.99, 0.992, 0.995, 0.999, 1), na.rm = T)
polII_color <- colorRamp2(
breaks = c(0, quantile(polII_log2_mat, c(0.5, 0.8, 0.9, 0.92, 0.95, 0.97, 0.99, 0.995, 0.999))),
colors = c("white", RColorBrewer::brewer.pal(n = 9, name = "RdPu"))
)
# colorRamp2(breaks = quantile(polII_log2_mat, 0, 0.99),colors = c("white", "red"))
if(!is.null(htColor)){
polII_color <- htColor
}
allPlots <- list()
firstPlot <- TRUE
## generate heatmaps
for(id in polII_ids){
ht <- signal_heatmap(log2_matrix = polII_log2_mat[, id, drop = FALSE],
col_title = id,
column_title_gp = gpar(fontsize = 12),
legend_title = "log2(polII_FPKM + 1)",
color = polII_color,
showLegend = firstPlot)
firstPlot <- FALSE
allPlots[[id]] <- ht
}
allPlots[["polII_color"]] <- polII_color
return(allPlots)
}
##################################################################################
lakhanp1/chipmine documentation built on March 6, 2021, 9:06 a.m.
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Defines functions get_expression_heatmap_list get_profile_plot_list multi_profile_plots
Documented in get_expression_heatmap_list get_profile_plot_list multi_profile_plots
##################################################################################
## function to get a heatmap list of provided TF, polII samples to be used directly for plotting
#' \code{EnrichedHeatmap} plots and \code{ComplexHeatmaps} for multiple samples
#'
#' This method generates profile heatmaps for multiple samples. Optionally, if the sample list
#' has any polII samples, it also generate a heatmap for the polII expression values.
#'
#' @param exptInfo experiment info as data frame with information like sampleID, type, path etc
#' @param genesToPlot A vector of gene IDs which are to be plotted
#' @param clusters Dataframe with cluster information. Two columns must be present in this
#' dataframe: 'cluster', 'geneId'. Default: NULL
#' @param drawClusterAn Logical: Whether to add row annotation heatmap to heatmap list. Default: TRUE
#' @param clusterColor cluster annotation color information. Default: NULL
#' @param clustOrd A character vector of cluster order in the plot. If not provided,
#' clusters are arranged as per character sort order
#' @param profileColors a named list of color objects for each of the sample. Color for profile
#' heatmap should be generated by colorRamp2
#' @param matSource Method by which profile matrix was generated. One of \emph{deeptools, miao,
#' normalizedmatrix}. Default: normalizedmatrix
#' @param targetType One of "region", "point". If targetType is "region", target is used to decide
#' the number of bins over region. Otherwise, for "point", a signle point matrix is expected where
#' the region is extracted around single point. Default: region
#' @param targetName Name to be used for target. Eg: "gene", "TSS", "TES", "summit" etc. default: gene
#' @param matBins A vector with four elements representing the column counts for up, body,
#' down regions and binSize for the profile matrix. Default: \code{c(200, 200, 100, 10)}
#' @param ylimFraction A named list with intensity scores to use as ylimit for top annotation.
#' If the value is single number, it has to be floating point number to extract the quantile and use
#' limit \code{[0, quantile(x)]}. If the value is numeric vector of length 2, the two numbers are used as lower
#' and upper limits for ylimit of top annotation. Default: NULL.
#' @param plotExpression Binry: whether to plot polII expression heatmap or not. Default: FALSE
#' @param expressionData an dataframe which has info: clustering, polII expression, TF binding
#' status for each gene etc. Default: NULL
#' @param keep Same as \code{EnrichedHeatmap::normalizeToMatrix}. First value is used as lower quantile
#' and any value in profile matrix less than lower quantile is set to lower quantile. Second value is
#' used as upper quantile and any value greater than upper quantile is set to upper quantile.
#' Default: \code{c(0, 1)}
#' @param expressionColor color object for polII expression heatmap
#' @param rasterize Binary: whether to rasterize the profile heatmap or not. By default this is set as TRUE
#' for multiple profile plots.
#' @param rasterQual Raster quality. This is the \code{raster_quality} argument \code{Heatmap} function. in Default: 5
#' @param ... Other arguments for EnrichedHeatmap function
#'
#' @return A list object with following elements:
#' \itemize{
#' \item heatmapList: a heatmap list object which has profile heatmaps and optionally expression heatmaps
#' \item profileHeatmaps: a named list of profile heatmaps generated by \code{EnrichedHeatmap}
#' \item expressionHeatmaps: a named list of polII signal heatmaps
#' \item plotGaps: a vector with required gaps between heatmaps while generating multiprofile plots
#' \item profileColors: a named list object with color scale used for each profile heatmap
#' \item expressionColor: a named list object with color scale used for each expression heatmap
#' }
#'
#' @export
#'
#' @examples NA
multi_profile_plots <- function(exptInfo,
genesToPlot,
clusters = NULL,
drawClusterAn = TRUE,
clusterColor = NULL,
clustOrd = NULL,
profileColors = NULL,
matSource = "normalizedmatrix",
targetType = "region",
targetName = "gene",
matBins = c(200, 200, 100, 10),
ylimFraction = NULL,
plotExpression = FALSE,
expressionData = NULL,
expressionColor = NULL,
keep = c(0, 1),
rasterize = TRUE,
rasterQual = 5,
...){
cat("Generating profile heatmaps...\n")
## profile heatmap list for all samples except first
profileList <- get_profile_plot_list(exptInfo = exptInfo,
cluster = clusters,
clusterColor = clusterColor,
clustOrd = clustOrd,
geneList = genesToPlot,
colorList = profileColors,
matrixSource = matSource,
matrixBins = matBins,
targetType = targetType,
targetName = targetName,
ylimFraction = ylimFraction,
keep = keep,
rasterPar = list(use = rasterize, qual = rasterQual),
...)
# cat("Done!!!\n")
expHtList <- list()
expHtList[["polII_color"]] <- expressionColor
if(isTRUE(plotExpression)){
cat("Generating expression heatmaps...\n")
## expression heatmap list
expHtList <- get_expression_heatmap_list(expDf = expressionData,
exptInfo = exptInfo,
genes = genesToPlot,
htColor = expressionColor)
# cat("Done!!!\n")
}
cat("Generating heatmap list object...\n")
## build the heatmap list for plotting
plotGaps <- numeric()
htList <- NULL
if(isTRUE(drawClusterAn)){
htList <- profileList[[ exptInfo$sampleId[1] ]][[ "rowGroupHt" ]]
plotGaps <- c(2)
}
profileColorList <- list()
for(i in 1:nrow(exptInfo)){
sampleID <- exptInfo$sampleId[i]
## add plot elements to the heatmap list
if(exptInfo$IP_tag[i] == "polII"){
## polII expression + profile
if(isTRUE(plotExpression)){
htList <- htList + expHtList[[sampleID]] + profileList[[sampleID]][["heatmap"]]
plotGaps <- append(plotGaps, c(2, 10))
} else{
## only polII profile
htList <- htList + profileList[[sampleID]][["heatmap"]]
plotGaps <- append(plotGaps, 10)
}
} else{
## TF profile
htList <- htList + profileList[[sampleID]][["heatmap"]]
plotGaps <- append(plotGaps, 10)
}
## add profile colors to profileColorList
profileColorList[[sampleID]] <- profileList[[sampleID]][["profileColor"]]
}
plotGaps <- head(plotGaps, -1)
returnList <- list(
"heatmapList" = htList,
"profileHeatmaps" = profileList,
"plotGaps" = plotGaps,
"profileColors" = profileColorList,
"expressionColor" = expHtList$polII_color
)
if(isTRUE(plotExpression)){
returnList[["expressionHeatmaps"]] <- expHtList
}
return(returnList)
}
##################################################################################
##################################################################################
## function to get the profile plots in list() using EnrichedHeatmap package
#' Multiple Enriched Heatmaps as list
#'
#' @param exptInfo experiment info as data frame with information like sampleID, type,
#' path etc
#' @param cluster Dataframe with cluster information. Two columns must be present
#' in this dataframe: 'cluster', 'geneId'. Default: NULL
#' @param clusterColor cluster annotation color information. Default: NULL
#' @param clustOrd A character vector of cluster order in the plot. If not provided,
#' clusters are arranged as per character sort order
#' @param geneList A vector of gene IDs which are to be plotted
#' @param colorList a named list of color objects for each of the sample. Color for
#' profile heatmap should be generated by colorRamp2
#' @param matrixSource Method by which profile matrix was generated. One of \emph{deeptools, miao,
#' normalizedmatrix}. Default: normalizedmatrix
#' @param matrixBins A numeric vector with four elements representing the column
#' counts for up, body, down regions and binSize for the profile matrix.
#' Default: \code{c(200, 200, 100, 10)}
#' @param targetType One of "region", "point". If targetType is "region", target is used to decide
#' the number of bins over region. Otherwise, for "point", a signle point matrix is expected where
#' the region is extracted around single point. Default: region
#' @param targetName Name to be used for target. Eg: "gene", "TSS", "TES", "summit" etc. default: gene
#' @param ylimFraction A named list with intensity scores to use as ylimit for top annotation.
#' If the value is single number, it has to be floating point number to extract the quantile and use
#' limit \code{[0, quantile(x)]}. If the value is numeric vector of length 2, the two numbers are used as lower
#' and upper limits for ylimit of top annotation. Default: NULL.
#' @param keep Same as \code{EnrichedHeatmap::normalizeToMatrix}. First value is used as lower quantile
#' and any value in profile matrix less than lower quantile is set to lower quantile. Second value is
#' used as upper quantile and any value greater than upper quantile is set to upper quantile.
#' Default: \code{c(0, 1)}
#' @param rasterPar rasterization parameters as list() with two elements: use, qual. Default:
#' \code{list(use = TRUE, qual = 5)}. \code{rasterPar$use} is used for \code{use_raster} argument and
#' \code{rasterPar$qual} is used for \code{raster_quality} argument of \code{Heatmap} function.
#' @param ... Other arguments for \code{EnrichedHeatmap} function
#'
#' @return A named list of Enriched Heatmap objects
#' @export
#'
#' @examples NA
get_profile_plot_list <- function(exptInfo,
cluster = NULL,
clusterColor = NULL,
clustOrd = NULL,
geneList,
colorList = NULL,
matrixSource = "normalizedmatrix",
matrixBins = c(200, 200, 100, 10),
targetType = "region",
targetName = "gene",
ylimFraction = NULL,
keep = c(0, 1),
rasterPar = list(use = TRUE, qual = 5),
...){
allPlots <- list()
## generate plot for each sample
for(i in 1:nrow(exptInfo)){
sampleName <- exptInfo$sampleId[i]
cat("Generating profile heatmap for:", sampleName, "...\n")
mat <- import_profile_from_file(file = exptInfo$matFile[i],
source = matrixSource,
signalName = sampleName,
selectGenes = geneList,
up = matrixBins[1],
target = matrixBins[2],
down = matrixBins[3],
binSize = matrixBins[4],
keep = keep,
targetType = targetType,
targetName = targetName)
qtDistr <- quantile(mat, c(seq(0, 0.9, by = 0.1), 0.95, 0.99, 0.992, 0.995, 0.999, 1), na.rm = T)
print(qtDistr)
## color: generate if colorList = NULL
tfCol <- colorRamp2(quantile(mat, c(0.50, 0.99), na.rm = T), c("white", "red"))
polIICol <- colorRamp2(quantile(mat, c(0.01, 0.5, 0.995), na.rm = T), c("blue", "white", "red"))
colFun <- tfCol
if(exptInfo$IP_tag[i] == "polII"){
colFun <- polIICol
}
## if the colors are provided with colorList argument, use those colors instead
if(!is.null(colorList[[sampleName]])){
colFun <- colorList[[sampleName]]
} else{
cat("Profile color for sample", sampleName, "not provided. Using internal default quantiles to generate color\n")
}
## build the profile heatmap
profile2 <- profile_heatmap(profileMat = mat,
signalName = exptInfo$profileName[i],
columnTitle = exptInfo$sampleName[i],
geneGroups = cluster,
profileColor = colFun,
clusterColor = clusterColor,
clusterOrder = clustOrd,
ylimFraction = ylimFraction[[sampleName]],
rasterPar = rasterPar,
...)
## append to the plot list
allPlots[[ sampleName ]] <- profile2
}
return(allPlots)
}
##################################################################################
##################################################################################
## get the pol-II expression heatmap in list() of class ComplexHeatmap for many samples
#' Multiple PolII expression heatmaps as list
#'
#' @param expDf a dataframe with PolII expression columns
#' @param exptInfo experiment info as data frame with information like sampleID, type, path etc
#' @param htColor heatmap color generated by \code{ColorRamp2}
#' @param genes A vector of gene IDs which are to be plotted
#'
#' @return A named list object with multiple Heatmaps
#' @export
#'
#' @examples NA
get_expression_heatmap_list <- function(expDf,
exptInfo,
genes,
htColor = NULL){
polII_ids <- exptInfo$sampleId[which(exptInfo$IP_tag == "polII")]
polII_expIds <- paste("is_expressed.", polII_ids, sep = "")
## select the gene of interst for plotting
geneSet <- data.frame(geneId = unique(genes), stringsAsFactors = F) %>%
dplyr::left_join(y = expDf, by = c("geneId" = "geneId"))
## clustering polII expression data
rownames(geneSet) <- geneSet$geneId
polII_mat <- as.matrix(geneSet[polII_ids])
polII_log2_mat <- log2(polII_mat + 1)
## polII Heatmap
quantile(polII_log2_mat, c(seq(0, 0.9, by = 0.1), 0.95, 0.99, 0.992, 0.995, 0.999, 1), na.rm = T)
polII_color <- colorRamp2(
breaks = c(0, quantile(polII_log2_mat, c(0.5, 0.8, 0.9, 0.92, 0.95, 0.97, 0.99, 0.995, 0.999))),
colors = c("white", RColorBrewer::brewer.pal(n = 9, name = "RdPu"))
)
# colorRamp2(breaks = quantile(polII_log2_mat, 0, 0.99),colors = c("white", "red"))
if(!is.null(htColor)){
polII_color <- htColor
}
allPlots <- list()
firstPlot <- TRUE
## generate heatmaps
for(id in polII_ids){
ht <- signal_heatmap(log2_matrix = polII_log2_mat[, id, drop = FALSE],
col_title = id,
column_title_gp = gpar(fontsize = 12),
legend_title = "log2(polII_FPKM + 1)",
color = polII_color,
showLegend = firstPlot)
firstPlot <- FALSE
allPlots[[id]] <- ht
}
allPlots[["polII_color"]] <- polII_color
return(allPlots)
}
##################################################################################
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