Renée X. de Menezes

I am a biostatistician with a passion for methods that solve data-motivated problems. A strong believer of model-based data analysis, I strive to build realistic (often parametric) models that avoid over-complexity. My main research interest lies in methods for simultaneous analysis of many high-dimensional data sets.

More recently I developed a method to normalize data from (whole-genome) genetic screens, including whole genome ones. It is especially useful to handle data from multiple cell lines, and when used it can help keep false positives generated by downstream analyses to the right level.

My current research interests include methods to analyse exon-level count data at the gene level, which should allow for finding events such as alternative splicing, as well as methods to analyse CRISPR screen data at the gene level, for all guide RNAs targeting the gene at once. I also work on methods to analyse microbiome data, and on methods that combine SNP and exon-level count data. I want to further develop these methods to allow for combined analyses of multiple types of high-throughput data.