R/pmdvis.R
In yufree/pmd: Paired Mass Distance Analysis for GC/LC-MS Based Non-Targeted Analysis and Reactomics Analysis
Defines functions
plotcn
plotsda
plotstdsda
plotstdrt
plotstd
plotpaired
plotrtg
Documented in
plotcn
plotpaired
plotrtg
plotsda
plotstd
plotstdrt
plotstdsda
#' Plot the retention time group
#' @param list a list from getpaired function
#' @param ... other parameters for plot function
#' @return NULL
#' @seealso \code{\link{getpaired}}, \code{\link{globalstd}}
#' @examples
#' data(spmeinvivo)
#' pmd <- getpaired(spmeinvivo)
#' plotrtg(pmd)
#' @export
plotrtg <- function(list, ...) {
std <- list$data
col <-
(grDevices::colorRampPalette(rev(
RColorBrewer::brewer.pal(11, "RdYlBu")
)))(length(unique(list$rtcluster)))
graphics::par(mfrow = c(2, 1), mar = c(4, 4, 2, 1) + 0.1)
graphics::plot(
list$rt,
list$mz,
xlab = 'retention time(s)',
ylab = 'm/z',
pch = 19,
col = col[list$rtcluster],
...
)
graphics::barplot(
table(list$rtcluster),
col = col[unique(list$rtcluster)],
ylab = 'peak numbers',
las = 2,
xlab = 'retention time group',
cex.names = 0.5
)
}
#' Plot the mass pairs and high frequency mass distances
#' @param list a list from getpaired function
#' @param index index for PMD value
#' @param ... other parameters for plot function
#' @return NULL
#' @seealso \code{\link{getpaired}}, \code{\link{globalstd}}
#' @examples
#' data(spmeinvivo)
#' pmd <- getpaired(spmeinvivo)
#' plotpaired(pmd)
#' @export
plotpaired <- function(list, index = NULL, ...) {
paired <- list$paired
if (is.null(index)) {
diffgroup <- as.numeric(as.factor(paired$diff2))
col <-
(grDevices::colorRampPalette(rev(
RColorBrewer::brewer.pal(11,
"RdYlBu")
)))(length(unique(paired$diff2)))
graphics::par(mfrow = c(2, 1),
mar = c(4, 4, 2,
1) + 0.1)
graphics::plot(
range(paired$rt),
range(paired$ms1,
paired$ms2),
type = "n",
xlab = "retention time(s)",
ylab = "m/z",
...
)
graphics::segments(
paired$rt,
paired$ms1,
paired$rt,
paired$ms2,
col = col[diffgroup],
lwd = 1.5
)
graphics::barplot(
table(list$paired$diff2),
col = col,
ylab = "Frequency",
las = 2,
xlab = "Paired mass distance",
cex.names = 0.618
)
} else {
paired <- paired[index,]
graphics::plot(
range(list$paired$rt),
range(list$paired$ms1,
list$paired$ms2),
type = "n",
xlab = "retention time(s)",
ylab = "m/z",
main = paste(paired$diff2[1],
"group"),
...
)
graphics::segments(
paired$rt,
paired$ms1,
paired$rt,
paired$ms2,
lwd = 1.5,
pch = 19
)
graphics::points(
paired$rt,
paired$ms1,
pch = 19,
col = grDevices::rgb(0, 0, 1, alpha = 0.318)
)
graphics::points(
paired$rt,
paired$ms2,
pch = 19,
col = grDevices::rgb(0, 0, 1, alpha = 0.318)
)
}
}
#' Plot the std mass from GlobalStd algorithm
#' @param list a list from getstd function
#' @return NULL
#' @seealso \code{\link{getstd}}, \code{\link{globalstd}}
#' @examples
#' data(spmeinvivo)
#' pmd <- getpaired(spmeinvivo)
#' std <- getstd(pmd)
#' plotstd(std)
#' @export
plotstd <- function(list) {
std <- list$stdmass
graphics::par(mfrow = c(1, 2), mar = c(4, 4, 2, 1) +
0.1)
col <- grDevices::rgb(0, 0, 1, alpha = 0.318)
graphics::plot(
list$rt,
list$mz,
xlab = "retention time(s)",
ylab = "m/z",
pch = 19,
col = col,
main = "all peaks"
)
graphics::plot(
std$rt,
std$mz,
xlab = "retention time(s)",
ylab = "m/z",
pch = 19,
col = col,
main = "GlobalStd peaks"
)
}
#' Plot the std mass from GlobalStd algorithm in certain retention time groups
#' @param list a list from getstd function
#' @param rtcluster retention time group index
#' @param ... other parameters for plot function
#' @return NULL
#' @seealso \code{\link{getstd}}, \code{\link{globalstd}},\code{\link{plotstd}},\code{\link{plotpaired}},\code{\link{plotstdsda}}
#' @examples
#' data(spmeinvivo)
#' pmd <- getpaired(spmeinvivo)
#' std <- getstd(pmd)
#' plotstdrt(std,rtcluster = 6)
#' @export
#'
plotstdrt <- function(list, rtcluster, ...) {
data <- list$data[list$rtcluster == rtcluster,]
if (length(data) > ncol(list$data)) {
msdata <- apply(data, 1, mean)
} else {
msdata <- mean(data)
}
mz <- list$mz[list$rtcluster == rtcluster]
rt <- stats::median(list$rt[list$rtcluster == rtcluster])
graphics::plot(
mz,
msdata,
type = "h",
xlab = paste("m/z",
"@", rt, "s"),
ylab = "Intensity",
...
)
stdmz <- list$stdmass$mz[list$stdmass$rtg == rtcluster]
index <- round(mz, 4) %in% round(stdmz, 4)
graphics::points(mz[index],
msdata[index],
type = "h",
lwd = 2,
col = "red")
}
#' Plot the std mass from GlobalStd algorithm in structure directed analysis(SDA) groups
#' @param list a list from getsda function
#' @param index index for PMD value
#' @param ... other parameters for plot function
#' @return NULL
#' @seealso \code{\link{getstd}}, \code{\link{globalstd}},\code{\link{plotstd}},\code{\link{plotpaired}},\code{\link{plotstdrt}}
#' @examples
#' data(spmeinvivo)
#' re <- globalstd(spmeinvivo, sda=TRUE)
#' plotstdsda(re)
#' @export
plotstdsda <- function(list, index = NULL, ...) {
sda <- list$sda
diffgroup <- as.numeric(as.factor(sda$diff2))
if (is.null(index)) {
col <- (grDevices::colorRampPalette(rev(
RColorBrewer::brewer.pal(11,
"RdYlBu")
)))(length(unique(diffgroup)))
graphics::par(mfrow = c(2, 1),
mar = c(4, 4, 2,
1) + 0.1)
graphics::plot(
range(sda$rt1, sda$rt2),
range(sda$ms1,
sda$ms2),
type = "n",
xlab = "retention time(s)",
ylab = "m/z",
...
)
graphics::segments(sda$rt1,
sda$ms1,
sda$rt2,
sda$ms2,
col = col[diffgroup],
lwd = 1.5)
graphics::points(
sda$rt1,
sda$ms1,
pch = 19,
col = grDevices::rgb(0,
0, 1, alpha = 0.318)
)
graphics::points(
sda$rt2,
sda$ms2,
pch = 19,
col = grDevices::rgb(0,
0, 1, alpha = 0.318)
)
graphics::barplot(
table(sda$diff2),
col = col,
ylab = "Frequency",
las = 2,
xlab = "Paired mass distances",
cex.names = 0.618
)
} else {
sda <- list$sda[index,]
graphics::plot(
range(list$sda$rt1, list$sda$rt2),
range(list$sda$ms1, list$sda$ms2),
type = "n",
xlab = "retention time(s)",
ylab = "m/z",
main = paste(sda$diff2[1],
"group"),
...
)
graphics::segments(sda$rt1,
sda$ms1,
sda$rt2,
sda$ms2,
lwd = 1.5,
pch = 19)
graphics::points(
sda$rt1,
sda$ms1,
pch = 19,
col = grDevices::rgb(0,
0, 1, alpha = 0.318)
)
graphics::points(
sda$rt2,
sda$ms2,
pch = 19,
col = grDevices::rgb(0,
0, 1, alpha = 0.318)
)
}
}
#' Plot the specific structure directed analysis(SDA) groups
#' @param list a list from getpmd function
#' @param ... other parameters for plot function
#' @return NULL
#' @seealso \code{\link{getstd}}, \code{\link{globalstd}},\code{\link{plotstd}},\code{\link{plotpaired}},\code{\link{plotstdrt}}
#' @examples
#' data(spmeinvivo)
#' re <- getpmd(spmeinvivo,pmd=78.9)
#' plotsda(re)
#' @export
plotsda <- function(list, ...) {
pmd <- list$pmd
graphics::par(mfrow = c(1, 1),
mar = c(4, 4, 2,
1) + 0.1)
graphics::plot(
range(pmd$rt1, pmd$rt2),
range(pmd$ms1,
pmd$ms2),
type = "n",
xlab = "retention time(s)",
ylab = "m/z",
...
)
graphics::segments(pmd$rt1,
pmd$ms1,
pmd$rt2,
pmd$ms2,
lwd = 1.5)
graphics::points(
pmd$rt1,
pmd$ms1,
pch = 19,
cex = 1.5
)
graphics::points(
pmd$rt2,
pmd$ms2,
pch = 19,
cex = 1.5
)
}
#' plot PMD KEGG network for certain compounds and output network average distance and degree
#' @param formula Chemical formula
#' @param name Compound name
#' @param pmd specific paired mass distances
#' @export
#' @examples
#' plotcn('C6H12O6','Glucose',c(2.016,14.016,15.995))
plotcn <- function(formula, name, pmd){
keggrall <- get("keggrall")
all <- keggrall[,c('formula1','formula2','pmd')]
# limit the pmd
all2 <- all[all$pmd %in% pmd,]
ms1 <- as.character(all2$formula1)
ms2 <- as.character(all2$formula2)
sdat <- unique(c(formula, ms2[ms1 %in% formula], ms1[ms2 %in% formula]))
seed <- NULL
while (!identical(sdat, seed)) {
seed <- sdat
sdat <- unique(c(sdat, ms2[ms1 %in% sdat], ms1[ms2 %in% sdat]))
}
df <- all2[ms1 %in% sdat | ms2 %in% sdat ,]
df2 <- df[!duplicated(df),]
pal <- grDevices::rainbow(length(pmd))
net <- igraph::graph_from_data_frame(df2,directed = FALSE)
dis <- igraph::mean_distance(net,directed = FALSE)
message(paste('Average distance of PMD network is', dis))
message(paste('Average degree',mean(igraph::degree(net))))
# igraph::V(net)$label.cex <- 1
graphics::plot(net,vertex.size =1,edge.width = 3,edge.color = pal[as.numeric(as.factor(igraph::E(net)$pmd))],vertex.label=ifelse(igraph::V(net)$name == formula,name,NA),vertex.label.dist=1,vertex.color=ifelse(igraph::V(net)$name == formula,'red','black'))
graphics::legend("topright",bty = "n",
legend=unique(igraph::E(net)$pmd),
fill=unique(pal[as.numeric(as.factor(igraph::E(net)$pmd))]), border=NA,horiz = FALSE,ncol = 2)
}
yufree/pmd documentation built on April 19, 2024, 9:31 a.m.
R Package Documentation
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Defines functions plotcn plotsda plotstdsda plotstdrt plotstd plotpaired plotrtg
Documented in plotcn plotpaired plotrtg plotsda plotstd plotstdrt plotstdsda
#' Plot the retention time group
#' @param list a list from getpaired function
#' @param ... other parameters for plot function
#' @return NULL
#' @seealso \code{\link{getpaired}}, \code{\link{globalstd}}
#' @examples
#' data(spmeinvivo)
#' pmd <- getpaired(spmeinvivo)
#' plotrtg(pmd)
#' @export
plotrtg <- function(list, ...) {
std <- list$data
col <-
(grDevices::colorRampPalette(rev(
RColorBrewer::brewer.pal(11, "RdYlBu")
)))(length(unique(list$rtcluster)))
graphics::par(mfrow = c(2, 1), mar = c(4, 4, 2, 1) + 0.1)
graphics::plot(
list$rt,
list$mz,
xlab = 'retention time(s)',
ylab = 'm/z',
pch = 19,
col = col[list$rtcluster],
...
)
graphics::barplot(
table(list$rtcluster),
col = col[unique(list$rtcluster)],
ylab = 'peak numbers',
las = 2,
xlab = 'retention time group',
cex.names = 0.5
)
}
#' Plot the mass pairs and high frequency mass distances
#' @param list a list from getpaired function
#' @param index index for PMD value
#' @param ... other parameters for plot function
#' @return NULL
#' @seealso \code{\link{getpaired}}, \code{\link{globalstd}}
#' @examples
#' data(spmeinvivo)
#' pmd <- getpaired(spmeinvivo)
#' plotpaired(pmd)
#' @export
plotpaired <- function(list, index = NULL, ...) {
paired <- list$paired
if (is.null(index)) {
diffgroup <- as.numeric(as.factor(paired$diff2))
col <-
(grDevices::colorRampPalette(rev(
RColorBrewer::brewer.pal(11,
"RdYlBu")
)))(length(unique(paired$diff2)))
graphics::par(mfrow = c(2, 1),
mar = c(4, 4, 2,
1) + 0.1)
graphics::plot(
range(paired$rt),
range(paired$ms1,
paired$ms2),
type = "n",
xlab = "retention time(s)",
ylab = "m/z",
...
)
graphics::segments(
paired$rt,
paired$ms1,
paired$rt,
paired$ms2,
col = col[diffgroup],
lwd = 1.5
)
graphics::barplot(
table(list$paired$diff2),
col = col,
ylab = "Frequency",
las = 2,
xlab = "Paired mass distance",
cex.names = 0.618
)
} else {
paired <- paired[index,]
graphics::plot(
range(list$paired$rt),
range(list$paired$ms1,
list$paired$ms2),
type = "n",
xlab = "retention time(s)",
ylab = "m/z",
main = paste(paired$diff2[1],
"group"),
...
)
graphics::segments(
paired$rt,
paired$ms1,
paired$rt,
paired$ms2,
lwd = 1.5,
pch = 19
)
graphics::points(
paired$rt,
paired$ms1,
pch = 19,
col = grDevices::rgb(0, 0, 1, alpha = 0.318)
)
graphics::points(
paired$rt,
paired$ms2,
pch = 19,
col = grDevices::rgb(0, 0, 1, alpha = 0.318)
)
}
}
#' Plot the std mass from GlobalStd algorithm
#' @param list a list from getstd function
#' @return NULL
#' @seealso \code{\link{getstd}}, \code{\link{globalstd}}
#' @examples
#' data(spmeinvivo)
#' pmd <- getpaired(spmeinvivo)
#' std <- getstd(pmd)
#' plotstd(std)
#' @export
plotstd <- function(list) {
std <- list$stdmass
graphics::par(mfrow = c(1, 2), mar = c(4, 4, 2, 1) +
0.1)
col <- grDevices::rgb(0, 0, 1, alpha = 0.318)
graphics::plot(
list$rt,
list$mz,
xlab = "retention time(s)",
ylab = "m/z",
pch = 19,
col = col,
main = "all peaks"
)
graphics::plot(
std$rt,
std$mz,
xlab = "retention time(s)",
ylab = "m/z",
pch = 19,
col = col,
main = "GlobalStd peaks"
)
}
#' Plot the std mass from GlobalStd algorithm in certain retention time groups
#' @param list a list from getstd function
#' @param rtcluster retention time group index
#' @param ... other parameters for plot function
#' @return NULL
#' @seealso \code{\link{getstd}}, \code{\link{globalstd}},\code{\link{plotstd}},\code{\link{plotpaired}},\code{\link{plotstdsda}}
#' @examples
#' data(spmeinvivo)
#' pmd <- getpaired(spmeinvivo)
#' std <- getstd(pmd)
#' plotstdrt(std,rtcluster = 6)
#' @export
#'
plotstdrt <- function(list, rtcluster, ...) {
data <- list$data[list$rtcluster == rtcluster,]
if (length(data) > ncol(list$data)) {
msdata <- apply(data, 1, mean)
} else {
msdata <- mean(data)
}
mz <- list$mz[list$rtcluster == rtcluster]
rt <- stats::median(list$rt[list$rtcluster == rtcluster])
graphics::plot(
mz,
msdata,
type = "h",
xlab = paste("m/z",
"@", rt, "s"),
ylab = "Intensity",
...
)
stdmz <- list$stdmass$mz[list$stdmass$rtg == rtcluster]
index <- round(mz, 4) %in% round(stdmz, 4)
graphics::points(mz[index],
msdata[index],
type = "h",
lwd = 2,
col = "red")
}
#' Plot the std mass from GlobalStd algorithm in structure directed analysis(SDA) groups
#' @param list a list from getsda function
#' @param index index for PMD value
#' @param ... other parameters for plot function
#' @return NULL
#' @seealso \code{\link{getstd}}, \code{\link{globalstd}},\code{\link{plotstd}},\code{\link{plotpaired}},\code{\link{plotstdrt}}
#' @examples
#' data(spmeinvivo)
#' re <- globalstd(spmeinvivo, sda=TRUE)
#' plotstdsda(re)
#' @export
plotstdsda <- function(list, index = NULL, ...) {
sda <- list$sda
diffgroup <- as.numeric(as.factor(sda$diff2))
if (is.null(index)) {
col <- (grDevices::colorRampPalette(rev(
RColorBrewer::brewer.pal(11,
"RdYlBu")
)))(length(unique(diffgroup)))
graphics::par(mfrow = c(2, 1),
mar = c(4, 4, 2,
1) + 0.1)
graphics::plot(
range(sda$rt1, sda$rt2),
range(sda$ms1,
sda$ms2),
type = "n",
xlab = "retention time(s)",
ylab = "m/z",
...
)
graphics::segments(sda$rt1,
sda$ms1,
sda$rt2,
sda$ms2,
col = col[diffgroup],
lwd = 1.5)
graphics::points(
sda$rt1,
sda$ms1,
pch = 19,
col = grDevices::rgb(0,
0, 1, alpha = 0.318)
)
graphics::points(
sda$rt2,
sda$ms2,
pch = 19,
col = grDevices::rgb(0,
0, 1, alpha = 0.318)
)
graphics::barplot(
table(sda$diff2),
col = col,
ylab = "Frequency",
las = 2,
xlab = "Paired mass distances",
cex.names = 0.618
)
} else {
sda <- list$sda[index,]
graphics::plot(
range(list$sda$rt1, list$sda$rt2),
range(list$sda$ms1, list$sda$ms2),
type = "n",
xlab = "retention time(s)",
ylab = "m/z",
main = paste(sda$diff2[1],
"group"),
...
)
graphics::segments(sda$rt1,
sda$ms1,
sda$rt2,
sda$ms2,
lwd = 1.5,
pch = 19)
graphics::points(
sda$rt1,
sda$ms1,
pch = 19,
col = grDevices::rgb(0,
0, 1, alpha = 0.318)
)
graphics::points(
sda$rt2,
sda$ms2,
pch = 19,
col = grDevices::rgb(0,
0, 1, alpha = 0.318)
)
}
}
#' Plot the specific structure directed analysis(SDA) groups
#' @param list a list from getpmd function
#' @param ... other parameters for plot function
#' @return NULL
#' @seealso \code{\link{getstd}}, \code{\link{globalstd}},\code{\link{plotstd}},\code{\link{plotpaired}},\code{\link{plotstdrt}}
#' @examples
#' data(spmeinvivo)
#' re <- getpmd(spmeinvivo,pmd=78.9)
#' plotsda(re)
#' @export
plotsda <- function(list, ...) {
pmd <- list$pmd
graphics::par(mfrow = c(1, 1),
mar = c(4, 4, 2,
1) + 0.1)
graphics::plot(
range(pmd$rt1, pmd$rt2),
range(pmd$ms1,
pmd$ms2),
type = "n",
xlab = "retention time(s)",
ylab = "m/z",
...
)
graphics::segments(pmd$rt1,
pmd$ms1,
pmd$rt2,
pmd$ms2,
lwd = 1.5)
graphics::points(
pmd$rt1,
pmd$ms1,
pch = 19,
cex = 1.5
)
graphics::points(
pmd$rt2,
pmd$ms2,
pch = 19,
cex = 1.5
)
}
#' plot PMD KEGG network for certain compounds and output network average distance and degree
#' @param formula Chemical formula
#' @param name Compound name
#' @param pmd specific paired mass distances
#' @export
#' @examples
#' plotcn('C6H12O6','Glucose',c(2.016,14.016,15.995))
plotcn <- function(formula, name, pmd){
keggrall <- get("keggrall")
all <- keggrall[,c('formula1','formula2','pmd')]
# limit the pmd
all2 <- all[all$pmd %in% pmd,]
ms1 <- as.character(all2$formula1)
ms2 <- as.character(all2$formula2)
sdat <- unique(c(formula, ms2[ms1 %in% formula], ms1[ms2 %in% formula]))
seed <- NULL
while (!identical(sdat, seed)) {
seed <- sdat
sdat <- unique(c(sdat, ms2[ms1 %in% sdat], ms1[ms2 %in% sdat]))
}
df <- all2[ms1 %in% sdat | ms2 %in% sdat ,]
df2 <- df[!duplicated(df),]
pal <- grDevices::rainbow(length(pmd))
net <- igraph::graph_from_data_frame(df2,directed = FALSE)
dis <- igraph::mean_distance(net,directed = FALSE)
message(paste('Average distance of PMD network is', dis))
message(paste('Average degree',mean(igraph::degree(net))))
# igraph::V(net)$label.cex <- 1
graphics::plot(net,vertex.size =1,edge.width = 3,edge.color = pal[as.numeric(as.factor(igraph::E(net)$pmd))],vertex.label=ifelse(igraph::V(net)$name == formula,name,NA),vertex.label.dist=1,vertex.color=ifelse(igraph::V(net)$name == formula,'red','black'))
graphics::legend("topright",bty = "n",
legend=unique(igraph::E(net)$pmd),
fill=unique(pal[as.numeric(as.factor(igraph::E(net)$pmd))]), border=NA,horiz = FALSE,ncol = 2)
}
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