Hi all, Does anyone have a function that is able to remove outliers from bead summary data? I am not a bioinformatian or a programmer, and I have no idea on how to change or alter the function used on Bead image data. I.e: par(mfrow=c(2,5)) for(i in 1:10){ o=findAllOutliers(BLData.bc, array=i) plotBeadLocations(BLData.bc, array=i, BeadIDs=o, main=an[i], SAM=TRUE, pch=".") } outliers = NULL for(i in 1:10) { outliers[i] = length(findAllOutliers(BLData.bc, array=i)) } x11() par(mai=c(2,1,0.2,0.1)) barplot(outliers/numBeads(BLData.bc)*100, main="Outliers per array", ylab="%", las=2, names=an) Thanks, Matt -- Matthew Vitalone B.Sc (Hons) PhD(progress) NHMRC Centre for Clinical Research Excellence in Renal Medicine Centre For Transplant and Renal Research Transplant Laboratory (Room 2175), Clinical Sciences Westmead Millennium Institute Darcy Road, Westmead, NSW, 2145. Sydney, Australia. Phone: (+61-2) 9845 8906 Mobile: 0416 041783 Hosp. Page: 27147 Fax: (+61-2) 9633 9351 Email: matthew_vitalone at wmi.usyd.edu.au _______________________________________________________________ This electronic message and any attachments may be confidential. If you are not the intended recipient of this message would you please delete the message and any attachments and advise the sender. Western Sydney Area Health Services (WSAHS) uses virus scanning software but excludes any liability for viruses contained in any email or attachment. This email may contain privileged and confidential infor...{{dropped:10}}

Dear Matt, The createBeadSummaryData() function in beadarray automatically removes outliers and summarises the intensities from the replicate beads when you specify method="illumina". This is done using Illumina's 3 MADs from the median rule to determine outliers by default. It is worth finding out whether outliers have already been removed from your bead-level data to avoid doing this step twice. If BeadScan has been run with the line <excludeoutliers>true</excludeoutliers> in the settings.xml file (located in the directory where BeadScan is installed), then you should use method="mean" instead, since the outliers will have already been removed from the bead-level output. Ask someone in your core facility to check on this if you're unsure. If you want the outliers included in your output, changing this 'true' to a 'false' should work. I hope this helps. Best wishes, Matt >Hi all, > >Does anyone have a function that is able to remove outliers from bead >summary data? I am not a bioinformatian or a programmer, and I have no >idea on how to change or alter the function used on Bead image data. > >I.e: >par(mfrow=c(2,5)) >for(i in 1:10){ > o=findAllOutliers(BLData.bc, array=i) > plotBeadLocations(BLData.bc, array=i, BeadIDs=o, main=an[i], SAM=TRUE, >pch=".") >} > >outliers = NULL >for(i in 1:10) { > outliers[i] = length(findAllOutliers(BLData.bc, array=i)) >} >x11() >par(mai=c(2,1,0.2,0.1)) >barplot(outliers/numBeads(BLData.bc)*100, main="Outliers per array", >ylab="%", las=2, names=an) > >Thanks, >Matt