highSCREEN (version 0.1)

zfactor.ssmd: title

Description

This function computes the Z-factor and strictly standardized mean difference (SSMD) of a given 96-well plate.

Usage

zfactor.ssmd(dat, pos.cont, neg.cont, MainPlate, triplicate)

Arguments

dat

Data frame as an output of the function $formatRESULT()$.

pos.cont

Designation of positive control.

neg.cont

Designation of negative control.

MainPlate

Specifies main plate.

triplicate

Specifies the triplicate.

Value

Returns a data frame with one row and the following columns:

MainPlate

Specifies the main plate.

triplicate

Specifies the triplicate.

ZFactor_Before

Specifies the Z-factor computed based on the "Before" data.

ZFactor_After

Specifies the Z-factor computed based on the "Before" data.

SSMD_Before

Specifies SSMD computed based on the "Before" data.

SSMD_After

Specifies SSMD computed based on the "Before" data.

Examples

set.seed(1234)
nc = 24
nr = 16

# create 1st triplicate of data matrix with compounds and controls
replicate1 = matrix(abs(rnorm(nr*nc)), nr, nc)

# create control map
cmap = data.frame(X1=c(rep("Control P", floor(nr/3)), 
rep(c("Control low", "Control med", "Control high"), 
(floor(nr/3)+nr-3*floor(nr/3))/3), rep("Control N", 
floor(nr/3))), X2=c(rep("Control N", floor(nr/3)), 
rep(c("Control low", "Control med", "Control high"), 
(floor(nr/3)+nr-3*floor(nr/3))/3), rep("Control P", floor(nr/3))))
cmap = cmap[seq(1,nr,2),]


# create 2nd triplicate of data matrix with compounds and controls
replicate2 = matrix(abs(rnorm(nr*nc)), nr, nc)

# create 3rd triplicate of data matrix with compounds and controls
replicate3 = matrix(abs(rnorm(nr*nc)), nr, nc)

# combine all triplicates for the before data
replicates_before = list(replicate1, replicate2, replicate3)
names(replicates_before) = c("Replicate1", "Replicate2", "Replicate3")

# create 1st triplicate of data matrix with compounds and controls
replicate1 = matrix(abs(rnorm(nr*nc)), nr, nc)

# create 2nd triplicate of data matrix with compounds and controls
replicate2 = matrix(abs(rnorm(nr*nc)), nr, nc)

# create 3rd triplicate of data matrix with compounds and controls
replicate3 = matrix(abs(rnorm(nr*nc)), nr, nc)

# combine all triplicates for the after data
replicates_after = list(replicate1, replicate2, replicate3)
names(replicates_after) = c("Replicate1", "Replicate2", "Replicate3")

# extract plate 1, triplicate 1
dat1 = extractplate(replicates_before, replicates_after, plate=1, replicate=1)
# extract plate 1, triplicate 2
dat2 = extractplate(replicates_before, replicates_after, plate=1, replicate=2)
# extract plate 1, triplicate 3
dat3 = extractplate(replicates_before, replicates_after, plate=1, replicate=3)

# no normalizion
datraw1 = normplate("Main Plate 1", dat1[["datbefore"]], dat1[["datafter"]], cmap,
 plate=1, triplicate=1, norm="raw")
datraw2 = normplate("Main Plate 1", dat2[["datbefore"]], dat2[["datafter"]], cmap,
 plate=1, triplicate=2, norm="raw")
datraw3 = normplate("Main Pltae 1", dat3[["datbefore"]], dat3[["datafter"]], cmap,
 plate=1, triplicate=3, norm="raw")

# combine 3 triplicates
datraw = rbind(datraw1, datraw2, datraw3)

# reformat result
datraw = formatRESULT(datraw, triplicate="Triplicate", score="score", t="Time")

# compute z-factor and ssmd for each raw compound, triplicate 1
zfactor.ssmd(datraw, "Control P", "Control N", "Main Plate 1", 1)