-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'm a bit confused/worried about duplicated spots on the Agilent bovine array, in particular how best to handle them in limma as I have technical rep dye-swaps. > #Get all non-control spots: > genes.idx <- which(RG$genes$ControlType == 0) > MA.none <- normalizeWithinArrays(RG[genes.idx,], method="none") > table(table(MA.none$genes$ProbeUID)) 2 6 21465 10 So 21465 probes are duplicated twice and 10 probes are duplicated 6 times. Does anyone have suggestions on how best to proceed given that I have technical rep dye-swaps? Also, how do I best handle those genes with multiple different probes? Simply average? Cheers, Nathan - -- - -------------------------------------------------------- Dr. Nathan S. Watson-Haigh OCE Post Doctoral Fellow CSIRO Livestock Industries Queensland Bioscience Precinct St Lucia, QLD 4067 Australia Tel: +61 (0)7 3214 2922 Fax: +61 (0)7 3214 2900 Web: http://www.csiro.au/people/Nathan.Watson-Haigh.html - -------------------------------------------------------- -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.9 (MingW32) Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org iEYEARECAAYFAkoKGXkACgkQ9gTv6QYzVL4RyACeNQUXJABLApt0qF8fU6Yn90On QY4AoJ+rYzYa8MGgmMt3mzzsBZ68+k8m =1+Hx -----END PGP SIGNATURE-----

Hi Nathan, I answered a very similar question about duplicated spots on arrays last Wednesday (May 6). You can find some code there. I recommend median of duplicated spot instead of average. God luck Peder Best regards Exiqon A/S Peder Worning, Ph.D. Senior Scientist, Biomarker Discovery -----Original Message----- From: bioconductor-bounces@stat.math.ethz.ch [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of Nathan S. Watson-Haigh Sent: Wednesday, May 13, 2009 2:51 AM To: bioconductor at stat.math.ethz.ch Subject: [BioC] Agilent duplicate spots and multiple probes per gene -----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'm a bit confused/worried about duplicated spots on the Agilent bovine array, in particular how best to handle them in limma as I have technical rep dye-swaps. > #Get all non-control spots: > genes.idx <- which(RG$genes$ControlType == 0) > MA.none <- normalizeWithinArrays(RG[genes.idx,], method="none") > table(table(MA.none$genes$ProbeUID)) 2 6 21465 10 So 21465 probes are duplicated twice and 10 probes are duplicated 6 times. Does anyone have suggestions on how best to proceed given that I have technical rep dye-swaps? Also, how do I best handle those genes with multiple different probes? Simply average? Cheers, Nathan - -- - -------------------------------------------------------- Dr. Nathan S. Watson-Haigh OCE Post Doctoral Fellow CSIRO Livestock Industries Queensland Bioscience Precinct St Lucia, QLD 4067 Australia Tel: +61 (0)7 3214 2922 Fax: +61 (0)7 3214 2900 Web: http://www.csiro.au/people/Nathan.Watson-Haigh.html - -------------------------------------------------------- -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.9 (MingW32) Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org iEYEARECAAYFAkoKGXkACgkQ9gTv6QYzVL4RyACeNQUXJABLApt0qF8fU6Yn90On QY4AoJ+rYzYa8MGgmMt3mzzsBZ68+k8m =1+Hx -----END PGP SIGNATURE----- _______________________________________________ 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