Quantro: a data-driven approach to guide the appropriate normalization method.
Our next meeting will be held on November 9th at noon in room 3160 of the Discovery Building. The chosen paper is on the Quantro method, a data-driven approach for choosing the best normalization methods. The paper is available from Genome Biology.
The abstract is as follows
Normalization is an essential step in the analysis of high-throughput data. Multi-sample global normalization methods, such as quantile normalization, have been successfully used to remove technical variation. However, these methods rely on the assumption that observed global changes across samples are due to unwanted technical variability. Applying global normalization methods has the potential to remove biologically driven variation. Currently, it is up to the subject matter experts to determine if the stated assumptions are appropriate. Here, we propose a data-driven alternative. We demonstrate the utility of our method (quantro) through examples and simulations. A software implementation is available from http://www.bioconductor.org/packages/release/bioc/html/quantro.html.
We look forward to seeing those who can join and feel free to begin the discussion below.