A function to identify the time of a change in the mean or variability of a metric

A function to identify the time of a change in the mean or variability of a metric

ChangePointEstimator(
  data = NULL,
  peptide,
  L = 1,
  U = 5,
  metric,
  normalization = TRUE,
  ytitle = "Change Point Plot - mean",
  type = "mean",
  selectMean = NULL,
  selectSD = NULL
)

Arguments

data

comma-separated (.csv), metric file. It should contain a "Precursor" column and the metrics columns. It should also include "Annotations" for each observation.

peptide

the name of precursor of interest.

L

Lower bound of the guide set.

U

Upper bound of the guide set.

metric

the name of metric of interest.

normalization

TRUE metric is standardized and FALSE if not standardized.

ytitle

the y-axis title of the plot. Defaults to "Change Point Plot - mean". The x-axis title is by default "QCno-name of peptide"

type

the type of the control chart. Two values can be assigned, "mean" or "variability". Default is "mean".

selectMean

the mean of a metric. It is used when mean is known. It is NULL when mean is not known. The default is NULL.

selectSD

the standard deviation of a metric. It is used when standard deviation is known. It is NULL when mean is not known. The default is NULL.

Value

A plot of likelihood statistics versus time per peptide and metric generated from CP.data.prepare data frame.

Examples

# First process the data to make sure it's ready to use
sampleData <- DataProcess(S9Site54)
#> Your data is ready to go!
head(sampleData)
#>    AcquiredTime Precursor   Annotations MinStartTime MaxEndTime
#> 1 9/19/11 13:14 VLVLDTDYK Not Available        24.30      25.08
#> 2 9/19/11 14:45 VLVLDTDYK Not Available        24.36      25.17
#> 3 9/19/11 16:15 VLVLDTDYK Not Available        24.19      24.96
#> 4 9/19/11 17:46 VLVLDTDYK Not Available        24.22      25.02
#> 5 9/19/11 19:16 VLVLDTDYK Not Available        24.27      25.05
#> 6 9/19/11 20:47 VLVLDTDYK Not Available        24.42      25.22
#>   BestRetentionTime TotalArea MaxFWHM missing
#> 1             24.62 116034248    0.29       0
#> 2             24.70 127339240    0.31       0
#> 3             24.53 110745576    0.31       0
#> 4             24.59 130619640    0.31       0
#> 5             24.62 113469472    0.30       0
#> 6             24.76 120836432    0.30       0
# Find the name of the peptides
levels(sampleData$Precursor)
#>  [1] "CAVVDVPFGGAK"   "DDGSWEVIEGYR"   "DGGIDPLVR"      "FFVAPFPEVFGK"  
#>  [5] "GFCGLSQPK"      "HLVDEPQNLIK"    "LVNELTEFAK"     "SLHTLFGDELCK"  
#>  [9] "TAAYVNAIEK"     "VGPLLACLLGR"    "VLDALDSIK"      "VLVLDTDYK"     
#> [13] "YNGVFQECCQAEDK" "YNLGLDLR"       "YSTDVSVDEVK"   
# Calculate change point statistics
ChangePointEstimator(data = sampleData, peptide = "VLVLDTDYK", metric = "BestRetentionTime")

ChangePointEstimator(
    data = sampleData, peptide = "VLVLDTDYK", metric = "BestRetentionTime",
    ytitle = "Change Point Plot - variability", type = "variability"
)

ChangePointEstimator(
    data = sampleData, peptide = "VLVLDTDYK", metric = "BestRetentionTime",
    selectMean = 27.78, selectSD = 8.19
)

ChangePointEstimator(data = sampleData, peptide = "DDGSWEVIEGYR", metric = "TotalArea")

ChangePointEstimator(
    data = sampleData, peptide = "DDGSWEVIEGYR", metric = "TotalArea",
    selectMean = 35097129, selectSD = 34132861
)

ChangePointEstimator(data = sampleData, peptide = "TAAYVNAIEK", metric = "MaxFWHM")