As low as 0.5 for pearson and 0.8 for spearman But I'm not holding up my data as a shining example Surely if there is a lot of natural variation in the biological system, then you're going to get large variation between biological replicates. -----Original Message----- From: Naomi Altman [mailto:naomi@stat.psu.edu] Sent: 28 February 2004 05:20 To: michael watson (IAH-C); 'rwin qian'; bioconductor@stat.math.ethz.ch Subject: RE: [BioC] cDNA microarray Questions What do you mean by "very low"? --Naomi At 04:24 AM 2/27/2004, michael watson (IAH-C) wrote: > >The correlation coefficients are very low. Is that the normal case? > >Do I need to delete some poor quality genes before any analysis and > >what rule should I use? > >Which correlation coefficient are you using? I regularly see very low >pearson correlation coefficients between biological replicates but that >can be put down to natural biological variation - no two organisms are the >same, right? BUT if you start seeing low correlations between technical >replicates (e.g. replicate samples from the same >animal/tissue/organ/whatever) then that indicates that you have a lot of >variation in your technology, which is bad. > >ON another note, I always find the Spearman Rank Correlation Coefficients >to be much higher. > >Mick > >_______________________________________________ >Bioconductor mailing list >Bioconductor@stat.math.ethz.ch >https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor Naomi S. Altman 814-865-3791 (voice) Associate Professor Bioinformatics Consulting Center Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111

I used the Spearman Rank Correlation Coefficients. One thing that I am not sure about is how to delete low quality genes after the normalization, especially for one spot-one gene in each array. Any insights from you will be appreciated! Darwin "michael watson (IAH-C)" <michael.watson@bbsrc.ac.uk> wrote: >The correlation coefficients are very low. Is that the normal case? >Do I need to delete some poor quality genes before any analysis and >what rule should I use? Which correlation coefficient are you using? I regularly see very low pearson correlation coefficients between biological replicates but that can be put down to natural biological variation - no two organisms are the same, right? BUT if you start seeing low correlations between technical replicates (e.g. replicate samples from the same animal/tissue/organ/whatever) then that indicates that you have a lot of variation in your technology, which is bad. ON another note, I always find the Spearman Rank Correlation Coefficients to be much higher. Mick --------------------------------- Yahoo! Search - Find what you’re looking for faster. [[alternative HTML version deleted]]

Many people delete low quality genes based on either comparison between background and foreground, comparison between the mean and median foreground, or visual inspection. I am reluctant to put a guess as to a good value for correlation based on the data I have worked with, which have been low-quality pilot studies with many spots deleted due to quality. However, it surely depends on the biological system - inbred lines in a highly controlled environment should be less variable, outbred and natural populations much more. Also, the correlations that you see in the literature are generally after normalization - global normalization will not affect the correlation, but lowess (or loess) certainly will. 50% seems low compared to what I have heard - but then, I have mostly heard about model organisms under controlled conditions. --Naomi At 10:12 AM 3/1/2004, michael watson (IAH-C) wrote: >As low as 0.5 for pearson and 0.8 for spearman >But I'm not holding up my data as a shining example >Surely if there is a lot of natural variation in the biological system, >then you're going to get large variation between biological replicates. > > >-----Original Message----- >From: Naomi Altman [mailto:naomi@stat.psu.edu] >Sent: 28 February 2004 05:20 >To: michael watson (IAH-C); 'rwin qian'; bioconductor@stat.math.ethz.ch >Subject: RE: [BioC] cDNA microarray Questions > > >What do you mean by "very low"? > >--Naomi > >At 04:24 AM 2/27/2004, michael watson (IAH-C) wrote: > > >The correlation coefficients are very low. Is that the normal case? > > >Do I need to delete some poor quality genes before any analysis and > > >what rule should I use? > > > >Which correlation coefficient are you using? I regularly see very low > >pearson correlation coefficients between biological replicates but that > >can be put down to natural biological variation - no two organisms are the > >same, right? BUT if you start seeing low correlations between technical > >replicates (e.g. replicate samples from the same > >animal/tissue/organ/whatever) then that indicates that you have a lot of > >variation in your technology, which is bad. > > > >ON another note, I always find the Spearman Rank Correlation Coefficients > >to be much higher. > > > >Mick > > > >_______________________________________________ > >Bioconductor mailing list > >Bioconductor@stat.math.ethz.ch > >https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor > >Naomi S. Altman 814-865-3791 (voice) >Associate Professor >Bioinformatics Consulting Center >Dept. of Statistics 814-863-7114 (fax) >Penn State University 814-865-1348 (Statistics) >University Park, PA 16802-2111 > >_______________________________________________ >Bioconductor mailing list >Bioconductor@stat.math.ethz.ch >https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor Naomi S. Altman 814-865-3791 (voice) Associate Professor Bioinformatics Consulting Center Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111