Dear Bioconductor Community,
from my analysis of an illumina microarray dataset (https://support.bioconductor.org/p/68307/#69270), i have acquired 5 DEG gene lists representing unique genes found DE between each specific biological treatment implemented vs the control group(DMSO). As i want to perform some unsupervised machine learning such as clustering and a possible heatmap of the intensities of these genes, im wondering how i should proceed based on the fact that are 5 contrasts:
One possible way i thought, is to subset from each contrast the top10 genes by abs(logFC), and then perform a heatmap with a clustering only on the rows(i.e genes) to identify genes that are similarly regulated, and/or possibly detect groups of genes that clustered together and thus regulated in a similar way across different treatments(possibly via heatmap.2). Or my cutoff is too arbitary and i could not possibly identify any significant patterns ?
Or alternatively should i intersect somehow the 5 DEG lists based on common probeIDs, and then use the common of all the contrasts to perform a heatmap only on these genes and only the treatments as samples for the visualization ?
Any recomendations, help or suggestions would be essential !!