Naive question: For calcNormFactors(), while using method="TMM", for normalization, can multiple independent biological replicates be used to normalize against? Help on calcNormFactors in edgeR seems to indicate using only one reference library / column (copied and pasted below). Could someone please clarify? Thanks, AksR Usage: calcNormFactors(object, method=c("TMM","RLE","upperquartile"), refColumn = NULL, logratioTrim = .3, sumTrim = 0.05, doWeighting=TRUE, Acutoff=-1e10, p=0.75) Arguments: object: either a ‘matrix’ of raw (read) counts or a ‘DGEList’ object method: method to use to calculate the scale factors refColumn: column to use as reference, only used when ‘method="TMM"’ logratioTrim: amount of trim to use on log-ratios ("M" values), only used when ‘method="TMM"’ sumTrim: amount of trim to use on the combined absolute levels ("A" values), only used when ‘method="TMM"’ doWeighting: logical, whether to compute (asymptotic binomial precision) weights, only used when ‘method="TMM"’ Acutoff: cutoff on "A" values to use before trimming, only used when ‘method="TMM"’ p: percentile (between 0 and 1) used to compute scale factors from, only used when ‘method="upperquartile"’ Details: ‘method="TMM"’ is the weighted trimmed mean of M-values (to the reference) proposed by Robinson and Oshlack (2010), where the weights are from the delta method on Binomial data. If ‘refColumn’ is unspecified, the library whose upper quartile is closest to the mean upper quartile is used. -- Anand K.S. Rao PhD candidate Plant Biology Graduate Group President Indian Graduate Student Association @ UCDavis University of California at Davis Davis, CA - 95616 USA -------------------------------------------- CTTATTGTTGAACTTOAATGGTGCTAATGATCCTCGTOTCTCCTGAACGT (translate THAT!) [[alternative HTML version deleted]]

Hi Anand, As I mentioned (in our offline conversation yesterday), I don't know of an obvious way to normalize against multiple samples. But, as I mentioned, I'm not convinced that it is necessary, or advisable. Maybe you can convince us why you want to do this? One could argue that even between biological replicates, variations (even artifacts) occur that would make the scaling factors different than 1. Best, Mark On 27.03.2012, at 03:48, Anand K S Rao wrote: > Naive question: > For calcNormFactors(), while using method="TMM", for normalization, can > multiple independent biological replicates be used to normalize against? > Help on calcNormFactors in edgeR seems to indicate using only one reference > library / column (copied and pasted below). > Could someone please clarify? > Thanks, > AksR > > Usage: > > calcNormFactors(object, method=c("TMM","RLE","upperquartile"), > refColumn = NULL, logratioTrim = .3, sumTrim = 0.05, doWeighting=TRUE, > Acutoff=-1e10, p=0.75) > > Arguments: > > object: either a ?matrix? of raw (read) counts or a ?DGEList? object > > method: method to use to calculate the scale factors > > refColumn: column to use as reference, only used when ?method="TMM"? > > logratioTrim: amount of trim to use on log-ratios ("M" values), only > used when ?method="TMM"? > > sumTrim: amount of trim to use on the combined absolute levels ("A" > values), only used when ?method="TMM"? > > doWeighting: logical, whether to compute (asymptotic binomial > precision) weights, only used when ?method="TMM"? > > Acutoff: cutoff on "A" values to use before trimming, only used when > ?method="TMM"? > > p: percentile (between 0 and 1) used to compute scale factors > from, only used when ?method="upperquartile"? > > Details: > > ?method="TMM"? is the weighted trimmed mean of M-values (to the > reference) proposed by Robinson and Oshlack (2010), where the > weights are from the delta method on Binomial data. If > ?refColumn? is unspecified, the library whose upper quartile is > closest to the mean upper quartile is used. > > > -- > Anand K.S. Rao > PhD candidate > Plant Biology Graduate Group > President > Indian Graduate Student Association @ UCDavis > University of California at Davis > Davis, CA - 95616 USA > -------------------------------------------- > CTTATTGTTGAACTTOAATGGTGCTAATGATCCTCGTOTCTCCTGAACGT > (translate THAT!) > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor ---------- Prof. Dr. Mark Robinson Bioinformatics Institute of Molecular Life Sciences University of Zurich Winterthurerstrasse 190 8057 Zurich Switzerland v: +41 44 635 4848 f: +41 44 635 6898 e: mark.robinson at imls.uzh.ch o: Y11-J-16 w: http://tiny.cc/mrobin