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New aggregateNet of no-significant-pathway for netVisual_diffInteraction #688

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New aggregateNet of no-significant-pathway for netVisual_diffInteraction #688

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32 changes: 22 additions & 10 deletions R/analysis.R
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Original file line number Diff line number Diff line change
Expand Up @@ -1931,6 +1931,7 @@ mergeInteractions <- function(object, group.merged) {
#' ligand.pct.2: threshold for the percent of expressed genes in the cells except for the defined 'positive' cell group
#'
#' @param receptor.pvalues,receptor.logFC,receptor.pct.1,receptor.pct.2 set threshold for receptor genes
#' @param non.significant.pathway Inherited feature from \code{\link{aggregateNet}}. Default set to NULL
#' @importFrom dplyr select group_by summarize groups
#' @importFrom stringr str_split
#' @importFrom BiocGenerics as.data.frame
Expand Down Expand Up @@ -1962,9 +1963,9 @@ subsetCommunication <- function(object = NULL, net = NULL, slot.name = "net",
sources.use = NULL, targets.use = NULL,
signaling = NULL,
pairLR.use = NULL,
thresh = 0.05,
thresh = NULL,
datasets = NULL, ligand.pvalues = NULL, ligand.logFC = NULL, ligand.pct.1 = NULL, ligand.pct.2 = NULL,
receptor.pvalues = NULL, receptor.logFC = NULL, receptor.pct.1 = NULL, receptor.pct.2 = NULL) {
receptor.pvalues = NULL, receptor.logFC = NULL, receptor.pct.1 = NULL, receptor.pct.2 = NULL, non.significant.pathway = NULL) {
if (!is.null(pairLR.use)) {
if (!is.data.frame(pairLR.use)) {
stop("pairLR.use should be a data frame with a signle column named either 'interaction_name' or 'pathway_name' ")
Expand All @@ -1990,7 +1991,7 @@ subsetCommunication <- function(object = NULL, net = NULL, slot.name = "net",
pairLR.use = pairLR.use,
thresh = thresh,
datasets = datasets, ligand.pvalues = ligand.pvalues, ligand.logFC = ligand.logFC, ligand.pct.1 = ligand.pct.1, ligand.pct.2 = ligand.pct.2,
receptor.pvalues = receptor.pvalues, receptor.logFC = receptor.logFC, receptor.pct.1 = receptor.pct.1, receptor.pct.2 =receptor.pct.2)
receptor.pvalues = receptor.pvalues, receptor.logFC = receptor.logFC, receptor.pct.1 = receptor.pct.1, receptor.pct.2 =receptor.pct.2, non.significant.pathway = non.significant.pathway)
} else if (object@options$mode == "merged") {
if (is.null(net)) {
net0 <- slot(object, "net")
Expand All @@ -2007,7 +2008,7 @@ subsetCommunication <- function(object = NULL, net = NULL, slot.name = "net",
pairLR.use = pairLR.use,
thresh = thresh,
datasets = datasets, ligand.pvalues = ligand.pvalues, ligand.logFC = ligand.logFC, ligand.pct.1 = ligand.pct.1, ligand.pct.2 = ligand.pct.2,
receptor.pvalues = receptor.pvalues, receptor.logFC = receptor.logFC, receptor.pct.1 = receptor.pct.1, receptor.pct.2 =receptor.pct.2)
receptor.pvalues = receptor.pvalues, receptor.logFC = receptor.logFC, receptor.pct.1 = receptor.pct.1, receptor.pct.2 =receptor.pct.2, non.significant.pathway = non.significant.pathway)
}
} else {
LR <- data.frame()
Expand All @@ -2022,7 +2023,7 @@ subsetCommunication <- function(object = NULL, net = NULL, slot.name = "net",
pairLR.use = pairLR.use,
thresh = thresh,
datasets = datasets, ligand.pvalues = ligand.pvalues, ligand.logFC = ligand.logFC, ligand.pct.1 = ligand.pct.1, ligand.pct.2 = ligand.pct.2,
receptor.pvalues = receptor.pvalues, receptor.logFC = receptor.logFC, receptor.pct.1 = receptor.pct.1, receptor.pct.2 =receptor.pct.2)
receptor.pvalues = receptor.pvalues, receptor.logFC = receptor.logFC, receptor.pct.1 = receptor.pct.1, receptor.pct.2 =receptor.pct.2, non.significant.pathway = non.significant.pathway)
}

}
Expand All @@ -2044,6 +2045,7 @@ subsetCommunication <- function(object = NULL, net = NULL, slot.name = "net",
#' @param thresh threshold of the p-value for determining significant interaction
#' @param datasets select the inferred cell-cell communications from a particular `datasets` when inputing a data frame `net`
#' @param ligand.pvalues,ligand.logFC,ligand.pct.1,ligand.pct.2 set threshold for ligand genes
#' @param non.significant.pathway Inherited feature from \code{\link{subsetCommunication}}. Default set to NULL
#'
#' ligand.pvalues: threshold for pvalues in the differential expression gene analysis (DEG)
#'
Expand All @@ -2066,19 +2068,27 @@ subsetCommunication_internal <- function(net, LR, cells.level, slot.name = "net"
sources.use = NULL, targets.use = NULL,
signaling = NULL,
pairLR.use = NULL,
thresh = 0.05,
thresh = NULL,
datasets = NULL, ligand.pvalues = NULL, ligand.logFC = NULL, ligand.pct.1 = NULL, ligand.pct.2 = NULL,
receptor.pvalues = NULL, receptor.logFC = NULL, receptor.pct.1 = NULL, receptor.pct.2 = NULL) {
receptor.pvalues = NULL, receptor.logFC = NULL, receptor.pct.1 = NULL, receptor.pct.2 = NULL, non.significant.pathway = NULL) {
if (!is.data.frame(net)) {
if(is.null(thresh)){
message("Threshold is set to 0.05")
thresh = 0.05
}
prob <- net$prob
pval <- net$pval
prob[pval >= thresh] <- 0
net <- reshape2::melt(prob, value.name = "prob")
colnames(net)[1:3] <- c("source","target","interaction_name")
net.pval <- reshape2::melt(pval, value.name = "pval")
net$pval <- net.pval$pval
# remove the interactions with zero values
net <- subset(net, prob > 0)
if(!is.null(non.significant.pathway)){
message("CellChat warning: non.sisgnificant pair included, none of the interactions for the pathway will be removed")
} else {
# remove the interactions with zero values
net <- subset(net, prob > 0)
}
}
if (!("ligand" %in% colnames(net))) {
pairLR <- dplyr::select(LR, c("interaction_name_2", "pathway_name", "ligand", "receptor" ,"annotation","evidence"))
Expand Down Expand Up @@ -2178,7 +2188,9 @@ subsetCommunication_internal <- function(net, LR, cells.level, slot.name = "net"
net$source_target <- paste(net$source, net$target, sep = "sourceTotarget")
# net$source_target_pathway <- paste(paste(net$source, net$target, sep = "_"), net$pathway_name, sep = "_")
net.pval <- net %>% group_by(source_target, pathway_name) %>% summarize(pval = mean(pval), .groups = 'drop')
net <- net %>% group_by(source_target, pathway_name) %>% summarize(prob = sum(prob), .groups = 'drop')
if(is.null(non.significant.pathway)){
net <- net %>% group_by(source_target, pathway_name) %>% summarize(prob = sum(prob), .groups = 'drop')
}
a <- stringr::str_split(net$source_target, "sourceTotarget", simplify = T)
net$source <- as.character(a[, 1])
net$target <- as.character(a[, 2])
Expand Down
10 changes: 6 additions & 4 deletions R/modeling.R
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Expand Up @@ -327,6 +327,7 @@ computeCommunProbPathway <- function(object = NULL, net = NULL, pairLR.use = NUL
#' @param remove.isolate whether removing the isolate cell groups without any interactions when applying \code{\link{subsetCommunication}}
#' @param thresh threshold of the p-value for determining significant interaction
#' @param return.object whether return an updated CellChat object
#' @param non.significant.pathway wheter the pathway to be aggregated was detected as not overrepresented (with no significant interaction) in group. Default is NULL, set to TRUE when intending to use \code{\link{netVisual_diffInteraction}} for comparing a not overrepresented pathway in group.
#' @importFrom dplyr group_by summarize groups
#' @importFrom stringr str_split
#'
Expand All @@ -340,7 +341,7 @@ computeCommunProbPathway <- function(object = NULL, net = NULL, pairLR.use = NUL
#'
#' @export
#'
aggregateNet <- function(object, sources.use = NULL, targets.use = NULL, signaling = NULL, pairLR.use = NULL, remove.isolate = TRUE, thresh = 0.05, return.object = TRUE) {
aggregateNet <- function(object, sources.use = NULL, targets.use = NULL, signaling = NULL, pairLR.use = NULL, remove.isolate = TRUE, thresh = 0.05, return.object = TRUE, non.significant.pathway = NULL) {
net <- object@net
if (is.null(sources.use) & is.null(targets.use) & is.null(signaling) & is.null(pairLR.use)) {
prob <- net$prob
Expand All @@ -356,10 +357,11 @@ aggregateNet <- function(object, sources.use = NULL, targets.use = NULL, signali
sources.use = sources.use, targets.use = targets.use,
signaling = signaling,
pairLR.use = pairLR.use,
thresh = thresh)
thresh = thresh,
non.significant.pathway = non.significant.pathway)
df.net$source_target <- paste(df.net$source, df.net$target, sep = "_")
df.net2 <- df.net %>% group_by(source_target) %>% summarize(count = n(), .groups = 'drop')
df.net3 <- df.net %>% group_by(source_target) %>% summarize(prob = sum(prob), .groups = 'drop')
df.net2 <- df.net %>% group_by(source_target) %>% dplyr::summarize(count = n(), .groups = 'drop')
df.net3 <- df.net %>% group_by(source_target) %>% dplyr::summarize(prob = sum(prob), .groups = 'drop')
df.net2$prob <- df.net3$prob
a <- stringr::str_split(df.net2$source_target, "_", simplify = T)
df.net2$source <- as.character(a[, 1])
Expand Down