Probe level data is used to examine the correlation structure among the N probes that have the same nominal target. Sometimes several probes are badly behaved or contain SNPs or indels. The well-behaved probes were then be used in GN1, at the user's discretion, to make an eigengene that sometimes performs quite a bit better than the Affymetrix probeset. Essentially, the user could design their own probesets. And the probe level data is quite fascinating to dissect some types of cis-eQTLsâthe COMT story I have attached is a good example. Here is figure 1 that exploits this unique feature:
Ideally, the probe level data would be in GN2 with the same basic functions as in GN1.
All we need in GN2/3 is a new table to display the probe level expression (mean) with their metadata (melting temperature, sequence, location, etc). The probeset ID is the Table header and name (the parent), and the probes in the table are the children. Using our now standard DataTable format should work well. We have a similar parent-child relation among traits with peptides and proteins. All of the peptides of a single protein are should have the same parent probeset/protein. And peptides could be entered as "probes" in the same way that we did for Affymetrix.
ArunâI wonder whether this hierarchy could be usefully combined to handle time-series data. Probably not ;-) In the case of probes and probesets there is almost never any overlap of probe sequenceâall are disjoint. That is also usually true of peptides and proteins.
Pjotr, the reason we have not added much probe level data to GN1 or GN2 is because we did not have the bandwidth. Arthur simply did not have time and I did not push the issue. Instead we just started loading the probe level data separately as if they were probesets. This is what we have done for peptide data and the reason that there are now "parallel" data setsâone labeled "protein" and another as "peptide" or as "gene level" and "exon level". We just collapse the hierarchy.