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Wanna know what kills him? I don't know if you watched Lord of the Rings, but it's pretty much Magic 101 that you DO NOT TOUCH EVIL RINGS OF POWER. Dumbledore found one, and like a retarded puppy licking a electrical outlet, he tried to use it. He survives his injuries for another year, which he spends failing to clue poor Harry in on what's going on. Finally he dies in front of Harry in the most traumatizing way possible.
July 2009 Archives
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Some examples of how to do some basic stuff in puppet.
So I've added a few new categories to the blog -- I'm looking to start dropping the sysadmin side of things, and move to more of a bioinformatics bent. To that end, I've decided to pick a couple of areas in the scientific computing field to start teaching myself a bit more about, while I get my act together and look to more formal education in the field.
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In statistics, resampling is any of a variety of methods for doing one of the following: 1. Estimating the precision of sample statistics (medians, variances, percentiles) by using subsets of available data (jackknifing) or drawing randomly with replacement from a set of data points (bootstrapping) 2. Exchanging labels on data points when performing significance tests (permutation tests, also called exact tests, randomization tests, or re-randomization tests) 3. Validating models by using random subsets (bootstrapping, cross validation) Common resampling techniques include bootstrapping, jackknifing and permutation tests.
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Chromosomal translocations are common in cancer, and in some cases may be causal in the progression of the disease. Using microarrays, in which the expression of thousands of genes are simultaneously measured, could potentially allow one to detect recurrent translocations for a particular cancer type. Standard statistical tests, such as the t-test are not suited for detecting these translocations, but a simple test based on robust centering and scaling of the data to help detect outlier samples, followed by a search for pairs of samples with mutually exclusive outliers, may be used to find genes involved in recurrent translocations. We have implemented this method, termed Cancer Outlier Profile Analysis (COPA) in an R package (that we call the copa package), and show its applicability on a publicly available dataset. AVAILABILITY: http://www.bioconductor.org
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# LEMMA is an R program that implements the RR model to analyze normalized microarray data. This version (1.1, 2009-05-27) supports two treatments and three-way classification: null genes, for which statistically there is no difference in expression between the two treatment groups; nonnull group #1 - genes that are significantly more expressed in group 1 than in group 2; and nonnull group #2 - genes that are significantly more expressed in group 2 than in group 1; or # two-way classification (null and nonnull genes, as in the LEMMA paper)
After a bunch of trial and error, and some semi-fruitless googling, finally have MPI BLAST built (for RHEL5U2 64-bit Server) with the Intel compilers. So that I don't lose this information completely (for when I need to rebuild at some point), I figured I'd stick it here (and maybe someone else could find it if they needed it). This isn't meant to be an exhaustive doc on how to get this configured and built on a variety of hardware and compilers, just what I needed to do to get this going in my own environment.
Continue reading Getting MPI BLAST built.
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The Korn shell uses two startup files, the .profile and the .kshrc. The .profile is read once, by your login ksh, while the .kshrc is read by each new ksh.
