My current cluster eliminates proteins that were never detected because I combined the data sets from silo 3 and silo 9 that contained only the corresponding silo’s abundant proteins. This means that when my cluster analysis is finished, I have uneven amounts of proteins for each silo. I want to create an even number of proteins per silo at the end of the cluster. This means I will need to edit the original raw data containing all of the silos rather than working off of the separate silo data sets.
After I do this, I will rerun the cluster analysis to get a new list of ‘unique’ proteins (unique proteins are defined as those that were in separate cluster groups based on temperature [ie. silo]). This final unique-proteins dataframe will be used for gene enrichment and to create heatmaps. I think a unique possible heatmap would be of parent terms based on the abundance of the proteins whose genes are annotated to that parent term.
I got my computer back so I made sure that all my files are up to date on all systems. I heavily modified my cluster code to create a more accurate unique-proteins dataframe since previously it had redundant and incorrect columns mixed in with correct columns. Scales for heatmaps are normalized abundance values.
Note that in this heatmap, the data has been:
- normalized (mean centered)
- mSet<-Normalization(mSet, "NULL", "NULL", "MeanCenter", ratio=FALSE, ratioNum=20)
- mSet<-PlotNormSummary(mSet, "norm_0_", "png", 72, width=NA)
- mSet<-PlotSampleNormSummary(mSet, "snorm_0_", "png", 72, width=NA)
If needed later: displaying two heatmaps by each other.