This is the 2023 website for the course Statistical methods in bioinformatics held by the University of Copenhagen.
Additional information will be given on the first day.
We will not be following a specific textbook closely but recommend Advances in Statistical Bioinformatics: Models and Integrative Inference for High-Throughput Data and Regression with linear predictors. See the notes for more information.
Bioinformatics is concerned with the study of inherent structure of biological information and statistical methods are the workhorses in many of these studies. Some of this inherent structure is very obvious and can be observed directly through correlations of patterns in high-dimensional data, while other patterns arise through more complicated underlying relationships.
This course covers some of the statistical models and methods suitable for analyzing high dimensional data - in particular high dimensional data that rely heavily on statistical methods The course will contain of equal parts theory and applications and consists of five full days of teaching and computer lab exercises. It is the intention that the participants will have a thorough understanding of the statistical methods and are able to apply them in practice after having followed this course.
A student who has met the objectives of the course will be able to:
You should bring a laptop as we will not have access to the computer rooms at the university.
Before the course starts you should make sure that you have installed the latest version of:
R and have installed the packages: kinship2, coxme, glmnet, MASS, MESS, cluster, data.table, lme4, minerva, and PTAk. This can be done from inside R using the command:
install.packages(c("kinship2", "glmnet", "coxme", "MESS", "MASS",
"cluster", "data.table", "lme4", "minerva", "PTAk"))
R Studio is also highly recommended but is not necessary.
We also need some packages from BioConductor, namely
edgeR
,
DESeq2
,vsn
,org.Hs.eg.db
. These
can be installed by running the following R chunk:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
requiredPackages = c('edgeR','DESeq2','vsn','org.Hs.eg.db')
for (p in requiredPackages) {
if(p %in% rownames(installed.packages()) == FALSE) {BiocManager::install(p)}
}
requiredPackages = c('ggplot2','dplyr','NMF','grDevices')
for (p in requiredPackages) {
if(p %in% rownames(installed.packages()) == FALSE) {install.packages(p)}
}
You could also try to install plink but that is not strictly necessary.
Installation instructions are available on the pages above.
Extra software might be installed through the course so make sure you have administrator/root access to your computer.
See the following map for the location of CSS. The room we will be in will be roughly located under the “C” in the text “Københavns Universitet Center for Sundhed og Samfund” (at least if you do not zoom in or out).
Claus Ekstrøm 2023