I finally got around to reading Ralph Vince’s latest The Leverage Space Trading Model (for a brief summary see this magazine article in Futures), and I’m happy to say that the book was very helpful in approach and example. I especially enjoye...
Monthly Archives: March 2011
Prune GWAS data in R
Hansong Wang, our biostats professor here at the Hawaii Cancer Center, generously gave me some R code that goes through a SNP annotation file (i.e. a mapfile) and selects SNPs that are at least a certain specified distance apart. You might want to do t...
Prune GWAS data in R
Hansong Wang, our biostats professor here at the Hawaii Cancer Center, generously gave me some R code that goes through a SNP annotation file (i.e. a mapfile) and selects SNPs that are at least a certain specified distance apart. You might want to do t...
Day #13 more plots, colors and loess smoothing
Yesterday I tried to insert some more R code into knime. scatterplot smoothed density library("geneplotter") ## from BioConductor require("RColorBrewer") ## from CRAN x1 <- matrix(rnorm(1e4), ncol=2) x2 <- matrix(rnorm(1e4, mean=3, sd=1.5...
Day #14 another R-course
So today I’m going to follow another R-course which is supposed to tell me more about Flowcytometry in R. I’ll keep you up to date
merge with solaR
The version 0.22 of solaR includes a new method, mergesolaR. It is designed to merge daily time series of several solaR objects. For example, we can obtain the daily irradiation of the whole set of meteorological stations of Madrid (Spain) and use this information to calculate the productivity of a grid connected PV system. It 
Example 8.32: The HistData package, sunflower plots, and getting data from R into SAS
This entry is mainly a promotion of the fascinating HistData R package. The package, compiled by the psychologist, statistician, and graphics innovator Michael Friendly, contains a number of small data sets of historical interest. These include data ...
Machine Learning Ex3 – Multivariate Linear Regression
Part 1. Finding alpha. The first question to resolve in Exercise 3 is to pick a good learning rate alpha. This require making an initial selection, running gradient descent and observing the cost function. Read More: 221 Words Totally
Two R functions for working with DNA alignments
Recently I wrote a couple of small functions as a result of work done by myself and others in my lab group. The first is a function that determines what sites in a sequence alignment are ambiguous (i.e. not A, G, C or T).
require(ape)This function utilises the bit-level coding scheme that...
data(woodmouse)
is.ambig x bases ambig ambig > 0
}
is.ambig(woodmouse)
Two R functions for working with DNA alignments
Recently I wrote a couple of small functions as a result of work done by myself and others in my lab group. The first is a function that determines what sites in a sequence alignment are ambiguous (i.e. not A, G, C or T).
require(ape)This function utilises the bit-level coding scheme that...
data(woodmouse)
is.ambig x bases ambig ambig > 0
}
is.ambig(woodmouse)
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
