Hallo Hai Qi, if I understand correctly, you ran a total of 200 thousand cells of the same sample through the machine twice. As you say the subpopulation is not that rare at 0.15%. I have often analysed samples with rare events at 0.05% of the total population with good precision,(granted the signal was way above background) and only saving 10,000 events. If you have a lot of debris or dead cells in the sample the %s can vary; so you can either: 1.use a ficoll gradient to clean up the sample. 2.reset your threshold value to cut out as much debris as possible. 3.live gate. 4.Run the cells slowly through the machine. 5.Make sure the machine is clean, as bits of junk stuck in the sample probe can effect your values. I might be wrong but I think saving 200,000 cells has to be more than ample to detect this subpopulation. Ann At 16:49 01.12.99 -0600, you wrote: > > >It is really not too rare, a cell population about 0.04% to 0.15%, while the >background is 0.01-0.05%. The problem is the variation among different >measurements, presumably due to the systematic error. For example, I had >10e7 total cells and ran 2*10e5 out of them for two times: one time I got >0.04% and the other time I got 0.15%. In order to have smaller variation, >obviously I have to increase my sample size, but the last thing I want to do >is to run through all 10e7 cells. Can anyone give me a handy statistical >method for estimating the sample size that makes a cost-effective >compromise? Thank you very much. > >Hai Qi >Dept. of Pathology, UTMB > >
This archive was generated by hypermail 2b29 : Wed Apr 03 2002 - 11:54:17 EST