Entries by Patrick K. Albers

Compare true and imputed genotypes by calculating R-squared

When performing imputation analyses, it is often useful to obtain measures for the imputation accuracy. Imputation typically estimates genotypes which were not observed in a genome-wide association study (GWAS) using whole-genome sequencing data as a reference, where genotypes that are missing in the sample are imputed based on the similarity of the observed genotypes to […]

Reduce size of IMPUTE2 genotype files

I am working a lot with IMPUTE2 for genotype imputation. Imputation generally predicts not-typed genotypes in a study sample by filling up the missing sites using a reference panel of sequence data (phased haplotypes). The file size of the data output, however, can become quite large. As I am working with simulated samples, of which […]


At this year’s annual meeting of the American Society of Human Genetics (ASHG), October 22-26 in Boston, I gave a talk on my current project: Meta-imputation. You can find the abstract here. This new method aims at combining most of the genetic information present in multiple reference panels for use in imputation. Imputation methods use […]


From our perspective to the largest scale measured, and then to the smallest scale measurable. This video illustrates the effect of adding or subtracting another zero on a given scale. The largest distance measurable in the observable universe was calculated to be about 47 billion lightyears; about . The smallest scale measurable, or at least […]

A simple progress-bar in R

A progress-bar is quite useful for displaying the current state of an iterating process, such as in a loop called using the for function in R. Below you can see my very quick and easy to use function for employing the progress-bar feature in R. Here is the code: To use the code, one simply has to […]