transpose = T/F in make.pheatmap() produced inconsistent results

[denvercal1234GitHub]

Hi there,

Thank you for the package.

When I plotted the same data and markers but with transpose=T or transpose = F, the expression for markers per cluster were different. For example, cluster 5 showed much more expression for more markers compared to that shown for cluster 5 when transpose = T.

Would you mind helping me clarify potential source of this inconsistency?

Note I used only a few markers in run.flowsom(), but I set use.cols in make.pheatmap and do.aggregate = to all cellular markers because I want to visualize the median expression of all markers and not only markers that were used in the clustering.

Thank you again.

exp_all_cellular.cols <- do.aggregate(F33_data.list_cell.dat_runflowsom_cellular.cols, use.cols=all_cellular.cols, by = "FlowSOM_metacluster")

make.pheatmap(exp_all_cellular.cols, "FlowSOM_metacluster", plot.cols = all_cellular.cols, transpose = F)

make.pheatmap(exp_all_cellular.cols, "FlowSOM_metacluster", plot.cols = all_cellular.cols, transpose = T)

[ghar1821]

It may have been due to the normalisation function applied to each column. By default, normalise parameter is set to TRUE, which I think transform the values between the range of 0 to 1 based on the min and max value in each column: x_ij=(x_ij-min(col_i) / (max(col_i) - min(col_i)) for cell j's marker i. When transforming, the columns and rows are swapped, which caused the min and max values to be different. Perhaps try setting normalise to FALSE?

[tomashhurst]

@ghar1821 spot on! @denvercal1234GitHub normalisation will run on the columns, regardless of whether it has been transposed or not.

[denvercal1234GitHub]

Thank you @tomashhurst and @ghar1821! I am confused. Would you mind clarifying whether the below statement is accurate?

Q1. If transpose = T, normalise=T, then does it mean the marker expression in the heatmap are first aggregated within a cluster with do.aggregate (with default parameters), then expression of each marker is normalised between 0-1 within each cluster?

Q2. Does transpose happens first or normalise happens first?