Hello All, I am working on Gene expression data analysis. As a beginner, I started working on Microarray expression data. I want to construct a co-expression network for my analysis. But before that, I want to check the quality of samples as well as the genes of my datasets. I have seen some methods like correlation plot, clustering for detecting the outliers at sample level and MAD score at the gene level, etc. when we are performing the outlier detection at sample level, do we need to consider the conditions like normal vs. disease samples. for sample level, I have used correlation heatmap plot and cluster dendrogram method and no outlier was observed in the outcome but what I observed that some normal samples are clustered with disease samples and vice-versa. As per my knowledge, it should not be like this. I am not able to understand how to interpret these results as I am new to this field. please help me with your expert opinion on this. I shall be thankful to you all.