It means transforming data to the Z-score aka standard score. The Z-score indicates how much a value deviates from the mean across all values and by this is a relative measure of e.g. gene expression, fold changes, whatever you put in. In R the scale function can do that for you, e.g. t(scale(t(matrix))) where matrix is the expression matrix with columns = samples and rows = genes. Data should be appropriately normalized, e.g. log2(normalized counts) with normalized counts e.g. coming from the DESeq2 or edgeR normalization or from transformations such as vst or rlog (the latter two already on log scale so no need to log them again).