I must be missing something here. I don't understand the point(s) being debated or the issues being raised. But I'll throw my two cents in anyway. Several years ago I was evaluating cell cycle analysis programs; ie, curve-fitting algorithms for analyzing histograms from cells with fluorescent stained DNA. I used BrdU incorporation as my Gold standard. After analyzing numerous data files there was only one program that consistently gave values for percentage of cells in G1, S and G2/M that agreed with the BrdU data. The program always gave a slightly LOWER S-phase (and correspondingly, slightly higher G1 and G2/M) than the BrdU incorporation data. In looking at DNA histograms of BrdU positive cells I noticed they usually showed a fairly discreet G2/M peak. It then occurred to me that the curve-fitting program was giving a BETTER measure of the percentages cell cycle compartments than the BrdU data. BrdU incorporation measures all cells in S-phase over the period of the BrdU pulse. That includes the "dim" BrdU positives, with "apparently G1 DNA content" that are in the earliest stages of S-phase to cells that completed S-phase very soon after the BrdU was added. These would be BrdU positive G2 cells. So the fact that the curve-fitting program was giving values for percent S-phase below those measured by BrdU incorporation makes perfect sense. DNA staining alone can't be resolve late-G1 cells from early-S and late-S from G2. That's why a GOOD curve-fitting algorithm will have an area of overlap at these transitions. It's a little alarming to hear Adam Treister say: >But for me, the role of data analysis software is to enable exploration >and to test >potential models, not only to churn existing models. Mark's message lists >valid uses >for the capability. Clearly there are limitations, but this is flow, so >what else is >new? The software is there only to calculate the numbers; it's up to the >biologist >to make sense of them. One would hope that the software calculations are providing realistic numbers so biologists can make sense of them. Esp. given the fact that I just ordered 3 copies of FlowJo. The last thing I need is a repeat of something like CellFit where the numbers calculated are heavily dependent on the model one chooses to fit the data. I wouldn't recommend you be too quick to discard the old models while you're exploring and testing "potential " models. td -- ============================================================================== Thomas M. Delohery |Internet: t-delohery@ski.mskcc.org Supervisor, Flow Cytometry Core Facility | Phone: (212) 639-8729 Memorial Sloan-Kettering Cancer Center | Fax: (212) 794-4019 1275 York Ave. Box 98 | New York, NY 10021 | ==============================================================================
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