normalising with bad slides
2
0
Entering edit mode
@andrew-einhorn-4221
Last seen 9.6 years ago
I have a set of 15 human gene st arrays that I am normalising. From analysis of the raw data, I can see that two of the slides are of very poor quality (signs of rna degradation, low pearson correlations etc). If I do an rma normalisation and include these two slides, will they effect the normalisation of the other slides. In other words, is it necessary to ignore these two slides in the rma step, or will including them make no difference. [[alternative HTML version deleted]]
• 761 views
ADD COMMENT
0
Entering edit mode
@james-w-macdonald-5106
Last seen 3 hours ago
United States
Hi Andrew, On 8/30/2010 3:12 AM, Andrew Einhorn wrote: > I have a set of 15 human gene st arrays that I am normalising. From > analysis of the raw data, I can see that two of the slides are of very poor > quality (signs of rna degradation, low pearson correlations etc). If I do > an rma normalisation and include these two slides, will they effect the > normalisation of the other slides. In other words, is it necessary to > ignore these two slides in the rma step, or will including them make no > difference. It *should* have minimal repercussions if you include the two bad slides. The normalization relies on the median value for each probe, so your poor quality chips will not likely be used. In addition, the model fitting process uses medians as well, so assuming that your poor quality chips return outlier values for each probeset, they won't be used for the model fit either. Best, Jim > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- James W. MacDonald, M.S. Biostatistician Douglas Lab University of Michigan Department of Human Genetics 5912 Buhl 1241 E. Catherine St. Ann Arbor MI 48109-5618 734-615-7826 ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues
ADD COMMENT
0
Entering edit mode
Mark Cowley ▴ 910
@mark-cowley-2951
Last seen 9.6 years ago
no problems Andrew -- apologies, I meant to reply all to keep this on the forum Jim's recent response is accurate as well, but I have seen situations where large numbers of bad arrays pollute the remaining good arrays. it is perhaps unclear whether 2 or 3 out of 15 will affect your results. in any case, I always re-normalise after removing poor quality arrays, i think it's safer that way (& easier for someone to repeat your analyses at a later date). cheers, Mark On 30/08/2010, at 11:00 PM, Andrew Einhorn wrote: > Apologies, I have worked the sub-setting thing out It actually > subsets fine the way I was doing it, don't know why the error was > coming up (had to restart R). > > On Mon, Aug 30, 2010 at 2:15 PM, Andrew Einhorn <andreweinhorn@gmail.com> > wrote: > Thanks Mark. So now I've identified my bad slides, how do I make a > subset of my original GeneFeatureSet (oligo class) to remove the bad > samples? I have 18 samples and want to remove 7,8 and 11. > > myFS <- read.celfiles("cel_files", full.names = TRUE) > # insert code to make myNewFS that excludes 7,8,11 > results <- rma(myNewFS) > > I have tried: > > myNewFS <- myFS[,1:6,9,10,12:18] > results <- rma(myNewFS) > > but it throws the following error: > "Error in function (classes, fdef, mtable) : > unable to find an inherited method for function "probeNames", for > signature "GeneFeatureSet"" > > Thanks again > > Andrew > > > > On Mon, Aug 30, 2010 at 1:29 PM, Mark Cowley > <m.cowley@garvan.org.au> wrote: > Hi Andrew, > If the bad arrays also look like outliers in a density plot of the > log2-PM probes, before normalisation, then yes, keeping those 2 bad > arrays in will pollute the signal from your other arrays -- due to > the quantile normalisation step in RMA. > > cheers, > Mark > On 30/08/2010, at 5:12 PM, Andrew Einhorn wrote: > >> I have a set of 15 human gene st arrays that I am normalising. From >> analysis of the raw data, I can see that two of the slides are of >> very poor >> quality (signs of rna degradation, low pearson correlations etc). >> If I do >> an rma normalisation and include these two slides, will they effect >> the >> normalisation of the other slides. In other words, is it necessary >> to >> ignore these two slides in the rma step, or will including them >> make no >> difference. >> >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor@stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > ----------------------------------------------------- > Mark Cowley, PhD > > Peter Wills Bioinformatics Centre > Garvan Institute of Medical Research, Sydney, Australia > ----------------------------------------------------- > > > [[alternative HTML version deleted]]
ADD COMMENT

Login before adding your answer.

Traffic: 534 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6