Hello, I am a beginner and have questions to ask for help. I have a cDNA microarray data with reference design and 4 biological replicates in each of the 2 groups. I want to do comparison between these two groups in terms of gene expression. After the normalization, I checked the correlation coefficient of log(ratio) between the replicates within each group. 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? My second question is what difference between function mt.maxT and mt.minP in “Multtest” package. My last question is how I can find the old mails in this mail listing since I just joined it and want to read some questions that might be useful. Thanks for the help! Darwin --------------------------------- [[alternative HTML version deleted]]

Hi Darwin, Q1. Sorry can't say for certain. Q2. Ge et al, '03 or Dudoit et al., '03 available from http://www.stat.berkeley.edu/~sandrine/publications.html may help you. Q3. Searchable Mail archives is one of the options under "Project" on the index (Left hand) of the Bioconductor web site. These links to http://www.liondb.org/biocond/ Good Luck, Aedin -----Original Message----- From: bioconductor-bounces@stat.math.ethz.ch [mailto:bioconductor-bounces@stat.math.ethz.ch]On Behalf Of rwin qian Sent: 25 February 2004 20:29 To: bioconductor@stat.math.ethz.ch Subject: [BioC] cDNA microarray Questions Hello, I am a beginner and have questions to ask for help. I have a cDNA microarray data with reference design and 4 biological replicates in each of the 2 groups. I want to do comparison between these two groups in terms of gene expression. After the normalization, I checked the correlation coefficient of log(ratio) between the replicates within each group. 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? My second question is what difference between function mt.maxT and mt.minP in ?Multtest? package. My last question is how I can find the old mails in this mail listing since I just joined it and want to read some questions that might be useful. Thanks for the help! Darwin --------------------------------- [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor

>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

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