vignettes/renderCurves.Rmd
renderCurves.RmdrenderAmpCurves and
renderMeltCurves function represents amplification and
melting data from real-time PCR experiments as curves based on
plotly package. Main advantage of using this functions
instead of regular plot renders is that it glued with
RDML package. Minimal usage recures only
GetFData(long.table = TRUE) function output. Also it has
interactive feature - fast curves hiding without total plot redraw.
library(shinyMolBio)
library(tidyverse)
library(RDML)
library(chipPCR)
# load RDML file
rdml <- RDML$new(system.file("/extdata/stepone_std.rdml", package = "RDML"))
renderAmpCurves(inputId = "firstLook", # Shiny input ID
label = "First Look", # optional plot label
ampCurves = rdml$GetFData(long.table = TRUE), # Amplification curves
interactive = FALSE
) Curve color can be directly provided by adding column color to ampCurves table or by choosing column that defines color with colorBy param.
renderAmpCurves(inputId = "color1",
"Color by Sample Name",
ampCurves = rdml$GetFData(long.table = TRUE),
colorBy = "sample", # sample name will define color
interactive = FALSE
)
renderAmpCurves(inputId = "color2",
"All 'red'",
ampCurves = rdml$GetFData(long.table = TRUE) %>%
mutate(color = "red"), # All curves will be red
interactive = FALSE
)## Warning in `[.data.table`(curves, , `:=`(curveName, sprintf("%s %s %s %s", :
## Invalid .internal.selfref detected and fixed by taking a (shallow) copy of the
## data.table so that := can add this new column by reference. At an earlier
## point, this data.table has been copied by R (or was created manually using
## structure() or similar). Avoid names<- and attr<- which in R currently (and
## oddly) may copy the whole data.table. Use set* syntax instead to avoid copying:
## ?set, ?setnames and ?setattr. If this message doesn't help, please report your
## use case to the data.table issue tracker so the root cause can be fixed or this
## message improved.Curve linetype can be setted by choosing column that defines linetype with linetypeBy param.
renderAmpCurves(inputId = "linetype",
"Different Linetypes",
ampCurves = rdml$GetFData(long.table = TRUE),
linetypeBy = "sample.type", # sample.type will define color
interactive = FALSE
) Threshold lines can be shown by choosing column that splits different threshold values with thBy param. Then input table have to contain quantFluor column.
# Create function for curves preprocessing
dataType$set("public", "Process",
function(thValue) {
# Subtract background
private$.adp$fpoints$fluor <-
CPP(self$adp$fpoints$cyc,
self$adp$fpoints$fluor,
bg.range = c(10,20))$y.norm
# Calc Cq by threshold method
cq <- th.cyc(self$adp$fpoints$cyc, self$adp$fpoints$fluor, r = thValue)[1, 1]
self$cq <- if(!is.na(cq)) cq else NULL
# Write threshold value
self$quantFluor <- thValue
},
overwrite = TRUE)
rdml <- RDML$new(system.file("/extdata/lc96_bACTXY.rdml", package = "RDML"))Loading experiment: ca1eb225-ecea-4793-9804-87bfbb45f81d run: 65aeb1ec-b377-4ef6-b03f-92898d47488b
# Manual threshold values for different targets
thValues <- c("bACT" = 0.03, "X" = 0.05, "Y" = 0.04, "IPC" = 0.01)
# Preprocess every curve
for (react in rdml$experiment[[1]]$run[[1]]$react) {
for (fdata in react$data) {
fdata$Process(thValues[fdata$tar$id])
}
}
tbl <- rdml$AsTable(quantFluor = data$quantFluor, # Add threshold values to table
cq = data$cq)
renderAmpCurves("th",
"Show Thershold Lines",
rdml$GetFData(tbl, long.table = TRUE),
colorBy = "target",
showCq = TRUE,
thBy = "target", # Add threshold lines (separated by targets)
interactive = FALSE) ## Warning: Ignoring 10 observationsYou can show Cq or Tm values on curves as markers
setting showCq = TRUE or showTm = TRUE. Then
input table have to contain cq or tm column, and
quantFluor for y values.
renderAmpCurves(inputId = "cq",
"Show Cq Values",
ampCurves = rdml$GetFData(tbl,
# Cq and quantFluor values are obtained
# from file on previous step
long.table = TRUE),
showCq = TRUE, # Add Cq markers to curves
colorBy = "sample",
interactive = FALSE
) ## Warning: Ignoring 10 observationsYou can add custom qouted plotly code by plotlyCode parameter. Note that you have to add value p inside your quoted code to link it with render output.
markTbl <- tbl %>%
filter(position %in% c("D03", "D07"),
target == "bACT")
renderAmpCurves("th",
"Show Thershold Lines",
rdml$GetFData(tbl, long.table = TRUE),
colorBy = "target",
plotlyCode = quote(
# Add Cq values for tubes D03 and D07 for target bACT as blue points
add_markers(p,
data = markTbl,
name = ~sample,
x = ~cq,
y = ~quantFluor,
marker = list(color = "blue",
size = 15)) %>%
# Set background color to light yellow
layout(paper_bgcolor = '#ffffe0',
plot_bgcolor = '#ffffe0')
),
interactive = FALSE)renderMeltCurves function provides all functionality described previosly in renderAmpCurves examples. Differences are showTm param instead of showCq and there is no thBy param.
# load RDML file
rdml <- RDML$new(system.file("/extdata/BioRad_qPCR_melt.rdml",
package = "RDML"))Loading experiment: All Wells run: Amp Step 3_FAM
run: Amp Step 3_Cy5Combining Bio-Rad runs
mdps <- rdml$GetFData(dp.type = "mdp", long.table = TRUE)
mdps[, diffFluor := c(0, diff(fluor)) * -1, by = fdata.name]
renderMeltCurves("melt",
"Show melting curves",
mdps,
fluorColumn = "diffFluor",
colorBy = "target",
interactive = FALSE)Individual curves can be hidden without plot redraw. Use
updateCurves function with fdata.name as
hideCurves param. Or highlighted with fdata.name as
highlightCurves param. Run
shinyMolBio::runExample("pcrPlateInput") to see this in
action. Curves hiding occures after wells selection at PCR plate and
higlighting after mouse hovering above PCR plate or details table.
Also curves can be hided or highlighted at the plot creation passing table with columns hideCurve and highlightCurve respectively.