receptLoss {receptLoss} | R Documentation |
This function allows you to identify genes with loss of expression
receptLoss(exprMatrNml, exprMatrTum, nSdBelow, minPropPerGroup)
exprMatrNml |
A matrix of expression values from normal tissue. Each row is a gene, and each column is a patient or sample. Genes should be in same order as exprMatrTum. |
exprMatrTum |
A matrix of expression values from tumor tissue. Each row is a gene, and each column is a patient or sample. Genes should be in same order as exprMatrNml. |
nSdBelow |
The number of SD below the mean of the adjacent normal tissue to set the boundary between tumor subgroups. |
minPropPerGroup |
A value between 0-1 that represents the minimum proportion of samples that should be present in each of the two subgroups (defined by the boundary set by nSdBelow) for a particular gene. |
a nx7 matrix, with n equaling the number of genes. The columns are as follows:
geneNm - the gene name
lowerBound - the lower bound, or the value 'nSdBelow' the mean of the normal tissue expression data.
propTumLessThBound - the proportion of tumor samples with expression levels less than 'lowerBound'
muAb - "mu above", the mean expression value of tumors greater than (ie above) the 'lowerBound'.
'muBl' - "mu below", the mean expression value of tumors less than (ie below) the 'lowerBound'.
'deltaMu' - the difference between 'muAb' and 'muBl'.
meetsMinPropPerGrp - a logical indicating whether the proportion of samples in each group is greater than that set by 'minPropPerGroup'.
exprMatrNml <- matrix(abs(rnorm(100, mean=2)), nrow=10) exprMatrTum <- matrix(abs(rnorm(100)), nrow=10) geneNames <- paste0(letters[seq_len(nrow(exprMatrNml))], seq_len(nrow(exprMatrNml))) rownames(exprMatrNml) <- rownames(exprMatrTum) <- geneNames nSdBelow <- 2 minPropPerGroup <- .2 rl <- receptLoss(exprMatrNml, exprMatrTum, nSdBelow, minPropPerGroup) head(rl)