Data Normalization

Pediatric acute myeloid leukemia (pAML) is characterized by heterogeneous cellular composition, driver alterations and prognosis. Characterization of this heterogeneity and how it affects treatment response remains understudied in pediatric patients. Researchers at the Michael Smith Genome Sciences Centre used single-cell ...

RNA-sequencing has become one of the most used high-throughput approaches to gain knowledge about the expression of all different RNA subpopulations. However, technical artifacts, either introduced during library preparation and/or data analysis, can influence the detected RNA expression levels. A ...

Next-generation sequencing technologies have enabled many advances across diverse areas of biology, with many benefiting from increased sample size. Although the cost of running next-generation...

Why do mRNA expression values need to be normalized? The unification of mRNA expression value measurements across studies, or the normalization of mRNA data, is a significant problem in biomedical and life science research. The abundance of transcripts is measured ...

Accurate identification and effective removal of unwanted variation is essential to derive meaningful biological results from RNA sequencing (RNA-seq)...

Constructing gene coexpression networks is a powerful approach for analyzing high-throughput gene expression data towards module identification, gene function prediction, and disease-gene...

In order to correctly decode phenotypic information from RNA-sequencing (RNA-seq) data, careful selection of the RNA-seq quantification measure is critical for inter-sample comparisons and for...

RNA-sequencing (RNA-seq) provides a comprehensive quantification of transcriptomic activities in biological samples. Formalin-Fixed Paraffin-Embedded (FFPE) samples are collected as part of routine clinical procedure, and are the most...

As the cost of single-cell RNA-seq experiments has decreased, an increasing number of datasets are now available. Combining newly generated and publicly accessible datasets is challenging due to non-biological signals, commonly known as batch effects...

The molecular characterization of immune subsets is important for designing effective strategies to understand and treat diseases. A team led by researchers from the University of Liverpool characterized...