Tail‐Robust Quantile Normalization

CQN (Conditional Quantile Normalization)

When to use Quantile Normalization?

Normalization and preprocessing are essential steps for the analysis of high-throughput data including next-generation sequencing and microarrays. Multi-sample global normalization methods, such as quantile normalization, have been successfully used to remove technical variation from noisy data. These methods rely on the assumption that observed global changes across samples are due to unwanted...

Subset Quantile Normalization Using Negative Control Features

Normalization has been recognized as a necessary preprocessing step in a variety of high-throughput biotechnologies. A number of normalization methods have been developed specifically for microarrays, some general and others tailored for certain experimental designs. All methods rely on assumptions about data characteristics that are expected to stay constant across samples, although some make ...

Supplementary Material to: When to use Quantile Normalization?

2 Description of high-throughput data used 5 2.1 Gene expression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1.1 RNA-Sequencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1.2 Microarrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2 DNA methy...

Removing technical variability in RNA-seq data using conditional quantile normalization

The ability to measure gene expression on a genome-wide scale is one of the most promising accomplishments in molecular biology. Microarrays, the technology that first permitted this, were riddled with problems due to unwanted sources of variability. Many of these problems are now mitigated, after a decade's worth of statistical methodology development. The recently developed RNA sequencing (RN...