inst/shiny-examples/MSstatsQCgui/data-validation.R

In MSstatsQCgui: A graphical user interface for MSstatsQC package

COL.BEST.RET <- "Retention Time"
COL.FWHM <- "Full Width at Half Maximum"
COL.TOTAL.AREA <- "Total Peak Area"
COL.PEAK.ASS <- "Peak assymetry"
#########################################################################################
# here we put a selection of most column names that users use. The first element of each vector should be the best name that
# we suggest users to use and  which our code is based on. for example "Retention Time" and "Full Width at Half Maximum" which are the first element
# of each vector in the list, are our suggestion so we wrote them in the fisrt place.
best_colnames <- list(
  c("AcquiredTime","Acquired.Time","time","creation date"),
  #c("Retention time","BestRetentionTime" ,"Best.RT","best retention time", "retention time","rt","best ret time","intensity","Best RT"),
  #c("Full width at half maximum","MaxFWHM","fwhm","max.fwhm", "Max FWHM"),
  #c("Total peak area","Total Area","TotalArea","total area","TA","T.Area"),
  c("MinStartTime","min start time","Min Start Time"),
  c("MaxEndTime", "max end time","Max End Time"),
  c("Precursor","PeptideSequence"),
  c("Annotations","anotations","anotation")
)
#### camelCaseSplit function ##############################################################################################
camelCaseSplit <- function(x) {
  # This function get a camelCase word and splits it.
  # Ex : camelCaseSplit("myComputerIsHere") ---> my Computer Is Here
  return(gsub("([a-z])([A-Z])", "\\1 \\L\\2", x, perl = TRUE))
}
#### punc_remove function #################################################################################################
punc_remove <- function(x){
  # This function removes any existing punctuation in your sentence or word and transfer it to space.
  # Ex1: punc_remove(Best.RT) --> Best RT     #Ex2: punc_remove(Best_RT) --> Best RT
  return(gsub("[[:punct:]///' ]", " ", x))
}
#### clearString function ###############################################################################################
clearString <- function(x){
  # This function, gets a word or setence, Splits it (if it is a camelCase), removes any existing punctuations, and transfer
  # all Upper Case letters to lower case letters.
  # Ex: clearString("myName_isSara.Taheri") --> my name is sara taheri
  return(tolower(punc_remove(camelCaseSplit(x))))
}
#### guessColumnName function ###########################################################################################
# This function receives the data and check the column names of data and changes the column names if it is not the
# same names as our suggested sample data to fit our suggested sample data

# # This function receives the data and check the column names of data and changes the column names if it is not the
# # same names as our suggested sample data to fit our suggested sample data

# guessColumnName <- function(x){
#
#   a <- clearString(x)
#
#   max_index <- 0
#   max <- -1
#   for(i in seq_len(length(best_colnames))){
#     col <- best_colnames[[i]]
#     for(j in seq_len(length(col))){
#       sim <- levenshteinSim(a,clearString(col[j]))
#       if(sim > max){
#         max <- sim
#         max_index <- i
#       }
#     }
#   }
#   if (max > 0.6) {
#     return(best_colnames[[max_index]][1])
#   }
#   else {
#     return(x)
#   }
# }
#############################################################################################################
input.sanity.check <- function(prodata) {
  error_message <- ""
  null_columns <- c()

  # get the column names and change them to the column names that we want (For example we want Retention Time but a user might use RT, this function auotomatically change RT to Retention Time)
  #colnames(prodata) <- unlist(lapply(colnames(prodata), function(x)guessColumnName(x)))


  ### conditions
  # check that the data includes all the requiered columns and if not tell user what column is missing
  # required_column_names <- c("Precursor","Retention Time","Full Width at Half Maximum","Total Peak Area","MinStartTime"
  #                            ,"MaxEndTime")
  required_column_names <- c("Precursor","Annotations")
  if(!("Annotations" %in% colnames(prodata))) {
    prodata[,"Annotations"] <- NA
    error_message <- paste(error_message, "Please create a column named Annotation and put all your metrics after this column.To see an example of a sample data click on the {Run with example data} button.\n\n")
  }
  provided_column_names <- colnames(prodata)
  # if(!all(required_column_names %in% provided_column_names)) {
  #   missedInput <- which(!(required_column_names %in% provided_column_names))
  #   error_message <- paste("ERROR : The required input(inputs) : ",
  #                          paste(required_column_names[missedInput], collapse = ", "),
  #                          " is(are) not provided in data set. Please add it to your data and try again.\n\n")
  # }

  # check that all columns other than Precursor and Acquired Time and Annotations are numeric.
  AfterannoColNum <- (which(colnames(prodata)=="Annotations")) + 1
  if(AfterannoColNum < ncol(prodata)) {
    #colNames <- colnames(prodata)
    for(i in  AfterannoColNum:ncol(prodata)) {
      if(is.numeric(prodata[,i]) == FALSE) {
        error_message <- paste(error_message, "All the values of", colnames(prodata)[i], "should be numeric and positive.\n\n")
      }
      #if(sum(is.na(prodata[,i])) > 0) {
      #null_columns <- c(null_columns,colNames[i])
      #}
    }
  }

  if(error_message != "") {
    #return(paste(error_message, "Please check the values to make sure all the inputs are numeric and positive and then try again."))
    return(paste(error_message))
  }
  # for custom metrics we are checking them to be numeric in QCMetrics in "find_custom_metrics" function and only accepting numeric columns after Annotation

  # if there is any missing value in data replace it with NA
  prodata[prodata==""] <- NA
  levels(prodata$Annotations) = c(levels(prodata$Annotations), "Not Available")
  prodata["Annotations"][is.na(prodata["Annotations"])] <- "Not Available"

  # some data migh have annotation column, some might not have. If it doesn't, we create an empty "Annotation" column at the very end column of the data

  # Define peak assymetry
  if("MinStartTime" %in% provided_column_names && "MaxEndTime" %in% provided_column_names) {
    peakAss <- 2*prodata$MinStartTime/(prodata$MaxEndTime+prodata$MinStartTime)
    # locate a new column named "Peak Assymetry" right after the column named "Annotation"
    #prodata.first <- prodata[,1:which(colnames(prodata)=="Annotations")]
    #prodata.first[,"Peak Assymetry"]<- peakAss
    #prodata <- cbind(prodata.first, prodata[,(which(colnames(prodata)=="MaxEndTime")+1):ncol(prodata), drop = FALSE])
    prodata[,"Peak assymetry"] <- peakAss
  }

  return(prodata)
}

### Input_checking function #########################################################################################
input_checking <- function(data){

  ## save process output in each step #### creating a log file ########### from Meena's code
#   allfiles <- list.files()
#
#   num <- 0
#   filenaming <- "./log/msstatsqc"
#   finalfile <- "msstatsqc.log"
#
#   while(is.element(finalfile,allfiles)) {
#     num <- num+1
#     finalfile <- paste(paste(filenaming,num,sep="-"),".log",sep="")
#   }

  #processout <- as.matrix(read.table("./log/sessionInfo.txt", header=T, sep="\t"))

  #write.table(processout, file=finalfile, row.names=FALSE)

  #processout <- rbind(processout, as.matrix(c(" "," ","MSstatsqc - dataProcess function"," "),ncol=1))

  data <- input.sanity.check(data)

  data <- data[complete.cases(data),] #work with complete cases

  return(data)
}