re-send message
To what extend would that variation be lower the positive regions are set a bit
further away from the background? As we know from the literature there can be
bursts in background signals (there was this article from someone using time as
a QC parameter).
Perhaps the histogram of time of a plot of time versus an appropriate parameter
gated on your rare event logic should reveal the timed appearance of the events
and reveal the statistical problem on a practical level. If your events are
well separated from the background and show an increase or decrease over time
you might consider effects of physical separation (settling...)
Regards
Gerhard
P.S. I wonder how my message will appear following our "outlook upgrade" today
References see either Shapiro or
LINDMO T, FUNDINGSRUD K
MEASUREMENT OF THE DISTRIBUTION OF TIME INTERVALS BETWEEN CELL PASSAGES IN
FLOW-CYTOMETRY AS A METHOD FOR THE EVALUATION OF SAMPLE PREPARATION
PROCEDURES
CYTOMETRY 2: (3) 151-154 1981
LINDMO T, FUNDINGSRUD K
MEASUREMENT OF THE DISTRIBUTION OF INTER-CELLULAR TIME INTERVALS REVEALS
NONIDEAL SAMPLE FLOW IN FLOW-CYTOMETRY
CYTOMETRY 2: (2) 112-112 1981
KUSUDA L, MELAMED MR
DISPLAY AND CORRECTION OF FLOW-CYTOMETRY TIME-DEPENDENT FLUORESCENCE
CHANGES
CYTOMETRY 17: (4) 340-342 DEC 1 1994
WATSON JV
TIME, A QUALITY-CONTROL PARAMETER IN FLOW-CYTOMETRY
CYTOMETRY 8: (6) 646-649 NOV 1987
-----Original Message-----
From: Howard Shapiro [SMTP:hms@shapirolab.com]
Sent: Monday, December 06, 1999 11:42 PM
To: Cytometry Mailing List
Subject: RE: rare events
Hai Qi reported finding 0.04% positives in one sample of 1/5 million cells
(I assume this is 200,000 cells) and 0.15% in another. In general, one can
use Poisson statistics in dealing with rare event analysis (or with counts
of small numbers of pretty much anything). In these cases, 0.01% of
200,000 is 20 cells, so the first sample had 80 positive cells and the
second had 300. The Poisson standard deviation for a count of n cells is
the square root of n, which is about 9 for the 80 cells and about 18 for
the 300. The two values are thus separated by several standard deviations,
which is to say that there is a statistically significant difference
between them. However, the statistics provide no information as to the
source of the difference. Since the cells came from the same pot, one
would suspect instrumental factors related to data collection and/or
analysis, unless there is reason to believe that a process such as
differential settling of the rare cell type would change the composition of
a sample aliquot with time. A mild degree of paranoia is probably an asset
when dealing with rare event analysis.
-Howard
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