Merge pull request #3 from MJS-708/v0.1.1

Release v0.1.1

Author: MJS-708

.gitignore

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+# History files
+.Rhistory
+.Rapp.history
+
+# Session Data files
+.RData
+
+# User-specific files
+.Ruserdata
+
+# Example code in package build process
+*-Ex.R
+
+# Output files from R CMD build
+/*.tar.gz
+
+# Output files from R CMD check
+/*.Rcheck/
+
+# RStudio files
+.Rproj.user/
+
+# produced vignettes
+vignettes/*.html
+vignettes/*.pdf
+
+# OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3
+.httr-oauth
+
+# knitr and R markdown default cache directories
+*_cache/
+/cache/
+
+# Temporary files created by R markdown
+*.utf8.md
+*.knit.md
+
+# R Environment Variables
+.Renviron
+
+#Folders
+data/
+tests/
+vignettes/

DESCRIPTION

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+Package: MSIprocessing
+Title: R package for processing MSI data - specifically extends Cardinal functionality
+Version: 0.1.0
+Author: Matthew Smith <[email protected]>
+Maintainer: Matthew Smith <[email protected]>
+Description: Offers MSI functionality such as normalisation
+License: MIT + file LICENSE
+Encoding: UTF-8
+LazyData: true
+Roxygen: list(markdown = TRUE)
+RoxygenNote: 7.1.1
+Imports: 
+    Cardinal,
+    dplyr,
+    ggplot2,
+    ggthemes,
+    grid,
+    impute,
+    scales,
+    tibble
+Depends: 
+    R (>= 2.10)
+Suggests: 
+    rmarkdown,
+    knitr,
+    testthat (>= 3.0.0)
+Config/testthat/edition: 3
+VignetteBuilder: knitr

LICENSE

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+# Generated by roxygen2: do not edit by hand
+
+export(calc_svds)
+export(checkAdductPair)
+export(createDatamatrix)
+export(create_xyMatrix)
+export(error)
+export(impute_scale)
+export(med)
+export(medianNorm)
+export(missing_values_df)
+export(myMean)
+export(myMed)
+export(normPixelsDF_anatomies)
+export(pixelDF_NormCompare)
+export(pixelsDF_NormCompare)
+export(ppm_limits)
+export(scale_colour_Publication)
+export(scale_fill_Publication)
+export(theme_Publication)
+import(ggplot2)
+import(ggthemes)
+import(scales)

NAMESPACE

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+################################################################
+########## General Cardinal extention Functions ################
+################################################################
+
+#' Function to create data matrix from MSI object
+#'
+#' @param MSIobject MSI object from Cardinal
+#' @param inputNA Whether to convert 0's in matrix to NA (default = T)
+#' @return dataframe with rows = ? cols = ?
+#'
+#' @export
+
+createDatamatrix <- function(MSIobject, inputNA = T){
+
+  MSIobject = as(MSIobject, "MSContinuousImagingExperiment")
+
+  df <- data.frame(spectra(MSIobject))
+
+  if(rownames(df)[1] == "1"){ # No row names
+    df <- df %>%
+      add_column(mz=as.numeric(mz(MSIobject))) %>%
+      column_to_rownames(var = "mz") %>%
+      rename_all(~sprintf("pixel_%s", 1:ncol(MSIobject)))
+  }
+
+  if(inputNA){
+    df <- replace(df, df==0, NA)
+  }
+
+  return(df)
+}
+
+
+
+#' Function for median normalisation
+#'
+#' @param x vector (relating to pixel spectrum)
+#'
+#' @return normalised spectrum vector
+#'
+#' @export
+medianNorm <- function(x){
+
+  pixelInt <- as.vector(x) %>%
+    ifelse(.==0, NA, .)
+
+  #print(pixelInt)
+
+  med <- median(pixelInt, na.rm=T)
+
+  #print(med)
+
+  newInt <- x / med
+  #print(newInt)
+
+  x[1:length(pixelInt)] <- newInt
+}
+#test <- daphProc[,1 ]
+
+
+
+#' Imputes Missing Values and scales MSI object
+#' @param MSIobject MSI object from Cardinal
+#'
+#' @return MSIobject with missing values imputed and datamatrix scaled.
+#'
+#' @export
+impute_scale <- function(MSIobject){
+
+  dataMatrix <- createDatamatrix(MSIobject)
+  print(nrow(dataMatrix)) # features
+  print(ncol(dataMatrix)) # pixels / samples
+  MVimputed <- missing_values_df(dataMatrix, rowmax = 0.99, colmax = 0.99)
+  #View(MVimputed[1:11, 1:11])
+  print(nrow(MVimputed))
+  print(ncol(MVimputed))
+
+  # Pareto scale (variance stabilisation)
+  scaled <- t(scale(t(MVimputed), center = T, scale = sqrt(apply(t(MVimputed), 2, sd, na.rm=T))))
+  # mean center (to mean of all features in sample)
+  # DIvide each feature by sd of feature - to stop high intense features skewing data (SD of intense features higher)
+
+  #View(scaled[1:11, 1:11])
+
+  #Create new object with intensity etc
+  MSIobject <- MSImagingExperiment(imageData=as.matrix(scaled), featureData=fData(MSIobject), pixelData=pData(MSIobject))
+
+  return(as(MSIobject, "MSProcessedImagingExperiment"))
+}
+
+
+
+#' Function to check colocalisation of suspected adduct pair
+#' 
+#' @param MSIobject MSI object from Cardinal
+#' @param mz1 First mz value to run colocalisation against
+#' @param mz2 Second mz value to check colocalisation score above given value
+#' @param threshold Threshold score to define whether features colocalise
+#' @param method Method to use for scoring colocalisation (Default = c("M1"))
+#' @param topn Number of top colocalised features to check (default = 20)
+#'
+#' @return Boolean whether mz feature colocalise
+#' @export
+
+checkAdductPair <- function(MSIobject, mz1, mz2, threshold, method = "M1", topn=20){
+
+  coloc <- data.frame( colocalized(MSIobject, mz = mz1, tolerance=20,
+                                    units="ppm", n= topn, sort.by = c(method) ) ) %>%
+    subset(correlation > threshold)
+
+  #View(coloc)
+
+  return(mz2 %in% coloc$mz)
+}
+
+
+#' Function to create x,y matrix for each feature - for feature selection.
+#' @param MSIobject MSI object from Cardinal
+#' @param mz mz channel to generate matrix for
+#'
+#' @return Data matrix for given mz; rows = y coordinate, cols = x-coordinate in the image
+#' @export
+
+create_xyMatrix <- function(MSIobject, mz){
+  matrix = slice(MSIobject, mz=mz) %>%
+    ifelse(. == 0, NA, .) %>%
+    ifelse(is.na(.), median(., na.rm=T), .) # impute MVs - using median
+  return(matrix)
+}
+#matrix = create_xyMatrix(MSIobject, mz=782.57)
+
+
+#' Function to create dataframe with information about specific pixel in specific anatomical region of MSI object
+#' @param MSIobject MSI object from Cardinal
+#' @param pixel pixel to select spectrum from
+#' @param anatomy label for the anatomical region pixel belongs to
+#' @param normalisation Which normalisation step has been applied to 'MSIobject'
+#' @param medianDF median spectrum to compare to
+#'
+#' @return Dataframe with headers: pixel, anatomy, mz, intensity (of mz feature), median, FC (to the median spectrum), normalisation
+#' @export
+
+pixelDF_NormCompare <- function(MSIobject, pixel, anatomy, normalisation, medianDF){
+
+  subsetObject <- MSIobject[, pixel]  # Subset data, to only include sample
+
+  pixelDF <- tibble(pixel=pixel, Anatomy = anatomy, mz= fData(subsetObject)@mz,
+                    intensity = createDatamatrix(subsetObject)[,1]) %>%
+    subset(mz %in% medianDF$mz) %>%
+    mutate(median = medianDF$median,
+           FC = intensity / median,
+           normalisation = normalisation)
+
+  return(pixelDF)
+}
+
+#' Function to create dataframe with information about all pixels in defined anatomical region of MSI object
+#'
+#' @param MSIobject MSI object from Cardinal
+#' @param pixels pixels to select spectra from
+#' @param anatomy label for the anatomical region pixels belongs to
+#' @param normalisation Which normalisation step has been applied to 'MSIobject'
+#' @param medianDF median spectrum to compare to
+#'
+#' @return Dataframe with headers: pixel, anatomy, mz, intensity (of mz feature), median, FC (to the median spectrum)
+#' @export
+
+pixelsDF_NormCompare <- function(MSIobject, pixels, anatomy, normalisation, medianDF){
+
+  pixelsDF <- tibble(pixel=numeric(), Anatomy = character(), mz= numeric(),
+                     intensity = numeric(), median = numeric(), FC = numeric())
+
+  for(pixel in pixels){
+    print(pixel)
+
+    pixelDF <- pixelDF_NormCompare(MSIobject, pixel, anatomy, normalisation, medianDF)
+    pixelsDF <- rbind(pixelsDF, pixelDF)
+    #print(head(pixelsDF))
+  }
+
+  return(pixelsDF)
+}
+
+
+#' Function to create dataframe with information about all pixels in several defined anatomical regions of MSI object
+#' Specifically used to compare distribution of feature distributions in different anatomical regions after normalisation
+#'
+#' @param MSIobject MSI object from Cardinal
+#' @param pixel_list list of pixel vectors from different anatomical regions
+#' @param anatomies vector of labels for the different anatomical regions pixels belongs to (same order as 'pixel_list')
+#' @param normalisation Which normalisation step has been applied to 'MSIobject'
+#' @param medianDF median spectrum to compare to
+#'
+#' @return Dataframe with headers: pixel, anatomy, mz, intensity (of mz feature), median, FC (to the median spectrum)
+#' @export
+normPixelsDF_anatomies <- function(MSIobject, pixel_list, anatomies, normalisation, medianDF){
+
+  pixelsDF <- tibble(pixel=numeric(), Anatomy = character(), mz= numeric(),
+                     intensity = numeric(), median = numeric(), FC = numeric())
+
+  for(i in 1:length(anatomies)){
+
+    pixels <- pixel_list[[i]]
+    anatomy <- anatomies[i]
+
+    print(anatomy)
+
+    tempDF <- pixelsDF_NormCompare(MSIobject = MSIobject, pixels = pixels, anatomy=anatomy,
+                                   normalisation=normalisation, medianDF= medianDF)
+
+    pixelsDF <- rbind(pixelsDF, tempDF)
+  }
+  return(pixelsDF)
+}
+
+

R/cardinalExtensionFunctions.R

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+#' Small MSI object pen ink
+#'
+#' A small MSI object from a sample of pen ink.
+#'
+#' @format MSI object with 265 features and 25 pixels
+"exampleMSI_object"