Hi,

I have tried to do module-trait analysis using module_trait_cor function. However, the correlation values I get on heatmap show opposite results to what I see with differential gene expression analysis. For example, if a gene is upregulated from DEG analysis based on the factor that I am analysing based on, with BioNERO that gene is in a module which is negatively correlated with the trait and it is for all genes. Is it normal? How to fix the issue? My metadata looks okay.

Thanks.

Hi,

First, differential gene expression and module-trait correlations are different things, because DGE performs pairwise comparisons between two levels of a discrete variable, while module-trait correlations don't.

Nevertheless, if a gene is up-regulated, it should not be in a module that is negatively correlated with the trait. Without looking at the data, it is very hard to think of what might have gone wrong, but I would suspect:

• Your differential expression analysis is wrong. A common mistake that people make (with DESeq2, for example) is to not relevel factor levels, so what they think is "up-regulated" is actually down-regulated;

• There is a problem with your metadata. If you are using a SummarizedExperiment object (say "se") and you are passing a metadata data frame, check if your metadata data frame matches colData(se), because module_trait_cor() ignores any argument to the metadata param if the expression data is a SummarizedExperiment object.