Description Usage Arguments Value Examples
description
1 2 | hits(dat.raw, dat.norm, s0="S0", s1="S1",
qc.mainplates, qc1.val=0.225, hit.val=3)
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dat.raw |
Data frame containing raw data as an output from formatRESULT(). |
dat.norm |
Data frame containing normalized data set as an output from formatRESULT(). |
s0 |
Specifies the name of the columns containing t0-specific scores. |
s1 |
Specifies the name of the columns containing t1-specific scores. |
qc.mainplates |
A vector containing names of main plates that passed QC. |
qc1.val |
Threshold value for QC1. |
hit.val |
Threshold value for identifying candidate hits, based on the mean of t1-specific scores. |
The function returns a data frame. Each row corresponds to a compound that passed QC1 and belongs to a plate that passed overall QC. The data frame contains the following columns:
ID |
Has the complete information to identify a compound or control. It contains information about the main plate, the quadrant/plate and the well. |
MainPlate |
Specifies the main plate to wich the compound/control belongs. |
Plate |
Specifies the quadrant/plate to wich the compound/control belongs. |
Norm |
Specifies the normalization method that was applied for the specific compound. |
well |
Specifies the location (row and column) of the compound/control in the quadrant. |
row |
Specifies the row location in the quadrant. |
col |
Specifies the column location in the quadrant. |
welltype |
Specifies if the well is compound or control. |
S0 |
Replicates of the score from the t0-specific data set. |
S1 |
Replicates of the score from the t1-specific data set. |
IND2 |
Indicator variable specifying if the compound passes (TRUE) or fails (FALSE) QC2. |
IND3 |
Indicator variable specifying if the compound passes (TRUE) or fails (FALSE) QC3. |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 | set.seed(1234)
nc = 24
nr = 16
# create 1st replicate of data matrix with compounds and controls
r1 = matrix(abs(rnorm(nr*nc)*0.01), 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 replicate of data matrix with compounds and controls
r2 = matrix(abs(rnorm(nr*nc)*0.01), nr, nc)
# create 3rd replicate of data matrix with compounds and controls
r3 = matrix(abs(rnorm(nr*nc)*0.01), nr, nc)
# combine all replicates for the t0-specific data
replicates_t0 = list(r1, r2, r3)
names(replicates_t0) = c("R1", "R2", "R3")
# create 1st replicate of data matrix with compounds and controls
r1 = matrix(abs(rnorm(nr*nc)), nr, nc)
# create 2nd replicate of data matrix with compounds and controls
r2 = matrix(abs(rnorm(nr*nc)), nr, nc)
# create 3rd replicate of data matrix with compounds and controls
r3 = matrix(abs(rnorm(nr*nc)), nr, nc)
# combine all replicates for the t1-specific data
replicates_t1 = list(r1, r2, r3)
names(replicates_t1) = c("R1", "R2", "R3")
# extract plate 1, replicate 1
dat1 = extractplate(replicates_t0, replicates_t1, plate=1, replicate=1)
# extract plate 1, replicate 2
dat2 = extractplate(replicates_t0, replicates_t1, plate=1, replicate=2)
# extract plate 1, replicate 3
dat3 = extractplate(replicates_t0, replicates_t1, plate=1, replicate=3)
# no normalizion
datraw1 = normplate("Main Plate 1", dat1[["dat0"]], dat1[["dat1"]], cmap,
plate=1, replicate=1, norm="raw")
datraw2 = normplate("Main Plate 1", dat2[["dat0"]], dat2[["dat1"]], cmap,
plate=1, replicate=2, norm="raw")
datraw3 = normplate("Main Pltae 1", dat3[["dat0"]], dat3[["dat1"]], cmap,
plate=1, replicate=3, norm="raw")
# combine 3 replicate
datraw = rbind(datraw1, datraw2, datraw3)
# reformat result
datraw = formatRESULT(datraw, replicate="Replicate", t="Time")
# c-score normalization
datnorm1 = normplate("Main Plate 1", dat1[["dat0"]], dat1[["dat1"]], cmap,
plate=1, replicate=1, norm="cscore",
poscont="Control P", negcont="Control N")
datnorm2 = normplate("Main Plate 1", dat2[["dat0"]], dat2[["dat1"]], cmap,
plate=1, replicate=2, norm="cscore",
poscont="Control P", negcont="Control N")
datnorm3 = normplate("Main Pltae 1", dat3[["dat0"]], dat3[["dat1"]], cmap,
plate=1, replicate=3, norm="cscore",
poscont="Control P", negcont="Control N")
# combine 3 replicates
datnorm = rbind(datnorm1, datnorm2, datnorm3)
# reformat result
datnorm = formatRESULT(datnorm, replicate="Replicate", t="Time")
# identify hits
head(hits(datraw, datnorm, qc.mainplates="Main Plate 1", qc1.val=0.225, hit.val=3))
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