normalization_via_DEseq_sizefactor.rtf

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\f0\fs24 \cf0 ## Write DESeq normalization function (using DESeq's size factor estimation)\
DESeq_norm <- function(m, sizefactors=NULL)\{\
  \
   library(DEseq2)\
\
  # create counts from intensity data in the required range\
  m_copy <- m\
  m_copy[is.na(m_copy)] <- 0\
  m_counts <- round(log2(m_copy+1)*1000,digit=0)\
  library(DESeq2)\
  \
  \
  # if no sizefactors are supplied, calculate them based on data\
  if (is.null(sizefactors))\{\
    # create an object summarized experiment class\
    dds <- DESeqDataSetFromMatrix(countData = m_counts,\
                                  colData = data.frame(condition=rep("group",times=ncol(m_counts))),\
                                  design =  ~ 1)\
    \
    # calculate normalization factors via DESeq's estimateSizeFactors(). Save them in working directory (so they can be used later on a different table of the same experiment if wanted) \
    sizefactors <- estimateSizeFactors(dds)$sizeFactor\
    if (!file.exists("Results"))\{\
      dir.create("Results")\
    \}\
    save(sizefactors, file=paste0(getwd(),"/Results/sizefactors.Rdata"))\
  \} else \{\
    sizefactors=sizefactors\
  \}\
  \
  \
  # perform normalization by column-wise multiplication with size-factors\
  m_counts_norm  <- sweep(m_counts, STATS=1/sizefactors, FUN="*", MARGIN = 2)\
  \
  # retransform to intensity range \
  m_norm <- 2^(m_counts_norm/1000) - 1\
  \
  # return normalized intensity matrix\
  return(m_norm)\
\}}