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<TITLE>Re: [RASMB] difference of p = 0.95, 0.68 and 0.55, the confidence level in the sedfit c(s) distribution</TITLE>
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<BLOCKQUOTE><FONT COLOR="#800000">Hi all<BR>
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In Peter's absence let me make one point which he (very correctly) makes concerning estimation of s values and relative concentrations. Which is that the c(s) distribution for each individual species in a mixture is <U>not</U> a gaussian distribution. Hence one should not do 'peak fitting' by the usual algorithms, in ORIGIN or anything else. As Jack very correctly says, it is numerical integration over appropriate ranges which you need.<BR>
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What <U>is</U> valid to a very good approximation is to fit multiple gaussians to the (least squares in SEDFIT) g(s) profile. Basically as per Walter Stafford's original approach. In our own experience we find this gives a more objective description of such systems, albeit - since it is better at resolving closely related species including dimers of lower M (i.e. more rapidly diffusing) monomers - the outcome can be rather less flattering to the perceived 'quality' of one's precious preparation!<BR>
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All best wishes to everyone<BR>
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Arthur<BR>
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Arthur Rowe<BR>
Lab at Sutton Bonington<BR>
tel: +44 115 951 6156<BR>
fax: +44 115 951 6157<BR>
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<BLOCKQUOTE>Since Peter is on a long vacation, I will attempt to answer your question. You can integrate the peaks by pressing the ctrl and I keys simultaneously which will give you a dialog box that states that you should hold the right mouse button down and draw a rectangle to cover the s range to be integrated. You will see once you do the integration you will obtain both the % of the loading signal in the integration range and the weight average s value. Also the results box states that this integration it is best done without regularization, confidence level of zero. Regularization gives the most parsimonious distribution for the confidence level that you set. Total removal of regularization may give you too many peaks that will merge at higher confidence levels. You can still integrate over multiple peaks in the s range you have selected and compare the result with integration of the distribution you obtain at higher confidence levels. In my experience the integration results over the same s range are comparable from no regularization to using settings of <FONT SIZE="2">p = 0.68 to 0.95. At the latter p selections you have the more realistic description of the sedimenting species. Hope that the above is clear.<BR>
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</FONT>Jack Lebowitz<BR>
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At 10:29 PM 7/12/2004 +0800, medakachou wrote:<BR>
<BLOCKQUOTE><FONT SIZE="2">Dear all,<BR>
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Recently, I'm analyzing the sedimentation velocity spectra by continuous c(s) distribution (SEDFIT). I've analyzed my data in three kind of confidence level: p = 0.95, 0.68 and 0.55 and the regularization method is maximum entropy. The s limit is 0.1 to 25S. I found every species is not well seperated (they just fuse together) in p = 0.95. In p = 0.68, the situation is better and the peaks are more significant. p= 0.55 can give me the highest resolution and every peak is very clear cut. Now the question is: if I want to calculate the area of peaks by Origin peak fitting module, which results should I use? I've check Schuck's paper and he suggests using p = 0.68 to 0.95 is enough. How about 0.55? I appreciate your response and suggestion.<BR>
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Sincerely,<BR>
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Chi-Yuan Chou<BR>
PhD student, the Institutes of Life sciences, National Defense Medical Center, Taipei, Taiwan<BR>
</FONT></BLOCKQUOTE><FONT SIZE="2">e-mail: r6243023@yahoo.com.tw<BR>
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