Flow group, and particularly for those of you who have called since my previous posting, my apologies. The correct reference should be: Rosenblatt, J.I., Hokanson, J.A., McLaughlin, S.R., Leary, J.F.: "A Theoretical Basis for Sampling Statistics Appropriate for the Detection and Isolation of Rare Cells Using Flow Cytometry and Cell Sorting" Cytometry 27: 233-238, 1997. In addition to rare cell sampling statistics this paper provides a perspective on the tradeoffs inherent in high-speed flow cytometry and cell sorting, and attempts to provide some advice on how fast is fast enough depending on what you are trying to do. It also provides some useful advice as to how stable the statistics are for small numbers of cells, since Poisson statistics are only an approximation that is not always accurate. While we present some mathematics for the "hard core" groups out there, we also provide some easy to interpret graphs to quickly and visually present the important take-home messages. If you find this useful (or not) please let me know. The only way we learn is to share experiences, and we very much want our work to be useful to others. These take-home messages really work in the practical world. We have found them very useful for guiding our own work as we develop a number of new high-throughput/rare-event applications. -- Jim Leary -----Original Message----- From: Leary, James F. [mailto:jleary@UTMB.EDU] Sent: Thursday, December 02, 1999 2:14 PM To: cyto-inbox Subject: RE: rare event Hai -- You might find our paper on rare cell sampling statistics helpful (Rosenblatt, J.I., Hokanson, J.A., McLaughlin, S.R., Leary, J.F.: "A Theoretical Basis for Sampling Statistics Appropriate for the Detection and Isolation of Rare Cells Using Flow Cytometry and Cell Sorting" Cytometry 26: 1-6; 1997). -- Jim Leary -----Original Message----- From: Qi, Hai [mailto:haqi@UTMB.EDU] Sent: Wednesday, December 01, 1999 4:49 PM To: cyto-inbox Subject: rare event 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 - 11:54:18 EST