## User: Christos Hatzis

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#### Posts by Christos Hatzis

<prev • 11 results • page 1 of 2 • next >
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... See 'combine' method for eSets: combine(eSet,eSet): Combine two eSet objects. To be combined, eSets must have identical numbers of featureNames, distinct sampleNames, and identical annotation -Christos -----Original Message----- From: bioconductor-bounces@r-project.org [mailto:bioconductor-bounce ...
written 8.6 years ago by Christos Hatzis110
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... One can get a reasonable answer on what housekeeping genes are only if the "invariance" of these genes is defined more clearly. For example, one can consider genes like actin or GAPDH as relatively invariant genes for normal cells as the encode for proteins needed for basic functions, which should ...
written 9.7 years ago by Christos Hatzis110
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... Hi Marien, You should be safe with Limma. That study concluded that shrinkage based methods that use regularized versions of the standard t statistic should be more efficient than the double filtering method (standard t-test & fold change). Limma uses a regularized or moderated t-statistic fo ...
written 9.9 years ago by Christos Hatzis110
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Comment: C: question about lmFit model
... I don't think that removing the high variance genes will improve the power to detect differentially expressed genes. Removing the low variance genes might though, as such genes would be less likely to exhibit large between groups sum of squares that would be associated with differential expression. ...
written 9.9 years ago by Christos Hatzis110
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Comment: C: question about lmFit model
... This strategy is bound to be less efficient, though. See a recent article on this subject. http://www.biomedcentral.com/1471-2105/10/402 -Christos Christos Hatzis, Ph.D. Nuvera Biosciences, Inc. 400 West Cummings Park, Suite 5350 Woburn, MA 01801 781-938-3844 -----Original Message----- From: b ...
written 9.9 years ago by Christos Hatzis110
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... The problem with the type of studies described in the original post is that you don't really have control over the design and thus experimental design principles are not helpful. The best approach might be to apply a simple normalization to all arrays and try to model potential batch effects throug ...
written 10.8 years ago by Christos Hatzis110
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... There is a slightly simpler way for merging two environments using l2e's second argument: e3 <- l2e(as.list(e1), e2) -Christos > -----Original Message----- > From: bioconductor-bounces at stat.math.ethz.ch > [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of > James W. ...
written 11.5 years ago by Christos Hatzis110
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... Hi Balazs, Does this do what you need? dat <- read.table("clipboard", header=TRUE) dat$pset <- gsub("([0-9])+$", "", rownames(dat)) # probe set means and number of probes dat.sum <- with(dat, aggregate(dat[, 1:2], by=list(pset), FUN="mean")) dat.sum\$n <- with(dat, aggregate(dat[, 1], ...
written 11.6 years ago by Christos Hatzis110
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... Have you checked the MAQC project? A link for the datasets used in this project is given on the main web site. A series of papers describing the different studies and datasets are publicly available from Nature Biotechnology (see link on the main MAQC page): http://www.fda.gov/nctr/science/centers ...
written 11.7 years ago by Christos Hatzis110
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... I don't know if this is doable within Bioconductor, but if a more manual process is acceptable, Stanford's Source database does map Clone IDs to gene ids, which can help with that process. http://genome-www5.stanford.edu/cgi-bin/source/sourceSearch -Christos > -----Original Message----- > F ...
written 11.8 years ago by Christos Hatzis110

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