Statistical Analysis

The enormous number of public gene expression data sets can turn into research gold when mined for any number of biological questions. But digging into the data of other researchers is often fraught by a lack of metadata. In particular, ...

Transcriptome sequencing (RNA-seq) is gradually replacing microarrays for high-throughput studies of gene expression. The main challenge of analyzing microarray data is not in finding differentially expressed genes, but in gaining insights into the biological processes underlying phenotypic differences. To interpret ...

A recent paper identified an artifact in multiple single-cell RNA-seq (scRNA-seq) data sets generated by the Fluidigm C1 platform. Specifically, Leng* et al. showed significantly increased gene expression in cells captured from sites with small or large plate output IDs. ...

Understanding the differences between microarray and RNA-Seq technologies for measuring gene expression is necessary for informed design of experiments and choice of data analysis methods. Previous comparisons have come to sometimes contradictory conclusions. Reseashers from Princeton University suggest that this ...

RNA-seq results often contain a PCA or MDS plot. This StatQuest explains how these graphs are generated, how to interpret them, and how to determine if the plot is informative or not.

A variety of pathway/gene-set approaches have been proposed to provide evidence of higher-level biological phenomena in the association of expression with experimental condition or clinical outcome. Among these approaches, it has been repeatedly shown that resampling methods are far preferable ...

Researchers at the FDA have developed methods to evaluate the stability of rat whole blood expression obtained from RNA sequencing (RNA-seq) and assess changes in whole blood transcriptome profiles in experiments replicated over time. Expression was measured in globin-depleted RNA ...

Nanopore DNA sequencing via transverse current has emerged as a promising candidate for third-generation sequencing technology. It produces long read lengths which could alleviate problems with assembly errors inherent in current technologies. However, the high error rates of nanopore sequencing ...

Previous comparisons between microarrays and RNA-Seq have come to sometimes contradictory conclusions, which researchers from Princeton University suggest result from a lack of attention to the intensity-dependent nature of variation generated by the technologies. To examine this trend, they carried ...

The advent of the NGS technologies has permitted profiling of whole-genome transcriptomes (i.e., RNA-Seq) at unprecedented speed and very low cost. RNA-Seq provides a far more precise measurement of transcript levels and their isoforms compared to other methods such as ...