Z-scores (heatmap) and statistics with replicates and outliers

My group performed a biological assay.The assay was performed for 6 different cell culture conditions (columns) and for 6 genes (rows). However, it was also performed 5 times (5 replicates) per each gene. An example of our data: Genes Condition 1 Condition 2 Gene 1 replicate 1 0.22 120 Gene 1 replicate 2 0.34 122 Gene 1 replicate 3 0.45 119 Gene 1 replicate 4 0.33 34 Gene1 replicate 5 0.55 90 Gene 2 replicate 1 12 0.1 Gene 2 replicate 2 19.3 0.45 Gene 2 replicate 3 23.4 NA Gene 2 replicate 4 11.7 0.89 Gene 2 replicate 5 12.4 0.1 And so on...for 6 genes and 6 conditions. Unfortunately we also have 2 NA values (for 2 conditions in gene 5 replicate 3, which doesn't mean the value is 0, it's just undetectable by the machine (below detectable value). I have already posted a question on stackoverflow about how to perform the analysis (z-score and heatmap) with R, and a very friendly user also suggested to ask here for a more statistical insight. The final heatmap will represent the changes of these genes expression in the different conditions. Basically in the end we want to compare the conditions based on their gene expressions, and maybe a pattern. In the end we would like to state "this cell culture condition has this gene pattern, which is different from the one of that cell culture condition". Our problem number 1 is the outlier. Replicate number 4 is in every condition an outlier. Should we exclude it? If so we would only have 4 replicates for the statistical analysis (ex. c…