Related Experiment Video
Updated: Jun 9, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
Published on: August 3, 2018
Neglecting the impact of normalization in semi-synthetic RNA-seq data simulations generates artificial false
Boris P Hejblum1,2, Kalidou Ba3,4, Rodolphe Thiébaut3,4,5
1Univ. Bordeaux, INSERM Bordeaux Population Health Research Center, U1219, INRIA SISTM, Bordeaux, F-33000, France. boris.hejblum@u-bordeaux.fr.
Abstract:
A recent study reported exaggerated false positives by popular differential expression methods when analyzing large population samples. We reproduce the differential expression analysis simulation results and identify a caveat in the data generation process. Data not truly generated under the null hypothesis led to incorrect comparisons of benchmark methods. We provide corrected simulation results that demonstrate the good performance of dearseq and argue against the superiority of the Wilcoxon rank-sum test as suggested in the previous study.
More Related Videos
Related Concept Videos
RNA-seq
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
Ribosome Profiling
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
Nonsense-mediated mRNA Decay
Usually, Upf3 binds to an Exon Junction Complex (EJC) at mRNA splice sites. If a ribosome fully translates the mRNA,...

