Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

50.9K
Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
50.9K
RNA-seq03:21

RNA-seq

11.9K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
11.9K
RNA Editing02:23

RNA Editing

9.8K
RNA editing is a post-transcriptional modification where a precursor mRNA (pre-mRNA) nucleotide sequence is changed by base insertion, deletion, or modification. The extent of RNA editing varies from a few hundred bases, in mitochondrial DNA of trypanosomes, to a just single base, in nuclear genes of mammals. Even a single base change in the pre-mRNA can convert a codon for one amino acid into the codon for another amino acid or a stop codon. This type of re-coding can significantly affect the...
9.8K
Distance Corrections01:15

Distance Corrections

285
To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
285
Power Factor Correction01:20

Power Factor Correction

510
The power transmission to a factory involves the transfer of apparent power, a combination of active and reactive power. The power factor measures how effectively electrical power is converted into useful work output. The ratio of the real power (KW) that does the work to the apparent power (KVA) supplied to the circuit.
510
RNA Interference01:23

RNA Interference

27.9K
RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
This process occurs naturally in cells, often through the activity of genomically-encoded microRNAs. Researchers can take advantage of this mechanism by introducing synthetic RNAs to deactivate specific genes for research or therapeutic purposes. For example, RNAi could be used...
27.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Mapping of in vivo cleavage sites uncovers a major role for yeast RNase III in regulating protein-coding genes.

eLife·2026
Same author

Dissociation of the nuclear basket triggers chromosome loss in aging yeast.

eLife·2025
Same author

The pseudogene RPS27AP5 expresses ubiquitin and ribosomal protein variants with potential roles in ribosome function.

Biochemistry and cell biology = Biochimie et biologie cellulaire·2025
Same author

RNase III cleavage sites spread across splice junctions enforce sequential snoRNA processing.

EMBO reports·2025
Same author

Mapping of in vivo cleavage sites uncovers a major role for yeast RNase III in regulating protein-coding genes.

bioRxiv : the preprint server for biology·2025
Same author

SnoBIRD: a tool to identify C/D box snoRNAs and refine their annotation across all eukaryotes.

Nucleic acids research·2025
Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026
Same journal

SpaMFG: a Spatial Multi-omics Integration Method based on Feature Grouping.

Bioinformatics (Oxford, England)·2026
Same journal

CSCN: Inference of Cell-Specific Causal Networks Using Single-Cell RNA-Seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

Sparse CCA-Based Mediation Analysis with High-Dimensional Exposures and Mediators.

Bioinformatics (Oxford, England)·2026
Same journal

Enhancing Cross-Context Generalization in Drug Perturbation Prediction with a Multimodal Conditional Diffusion Framework.

Bioinformatics (Oxford, England)·2026
Same journal

Primer Design through Submodular Function Estimation.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Jan 24, 2026

Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA
14:49

Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA

Published on: October 27, 2011

39.6K

CoCo: RNA-seq read assignment correction for nested genes and multimapped reads.

Gabrielle Deschamps-Francoeur1, Vincent Boivin1, Sherif Abou Elela2

  • 1Department of Biochemistry and RNA Group, Université de Sherbrooke, Sherbrooke, QC, Canada.

Bioinformatics (Oxford, England)
|May 30, 2019
PubMed
Summary
This summary is machine-generated.

Next-generation sequencing (NGS) for RNA expression analysis often misassigns reads from repetitive genes. The Count Corrector (CoCo) pipeline improves accuracy by reassigning these reads, salvaging over 15% of discarded data.

More Related Videos

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
05:07

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Published on: November 7, 2025

368
Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
06:33

Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding

Published on: October 11, 2018

7.2K

Related Experiment Videos

Last Updated: Jan 24, 2026

Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA
14:49

Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA

Published on: October 27, 2011

39.6K
Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
05:07

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Published on: November 7, 2025

368
Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
06:33

Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding

Published on: October 11, 2018

7.2K

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Next-generation sequencing (NGS) enables whole transcriptome analysis.
  • Challenges exist in accurately quantifying RNA expression due to read misassignment from nested and multi-copy genes.

Purpose of the Study:

  • To develop a computational pipeline, Count Corrector (CoCo), for improved RNA-seq read assignment.
  • To address the issue of read misassignment and loss in complex transcriptomes.

Main Methods:

  • CoCo utilizes a modified annotation file to identify nested genes.
  • It proportionally distributes multimapped reads across repetitive sequences.
  • The pipeline processes aligned RNA-seq reads for enhanced quantification.

Main Results:

  • CoCo salvages over 15% of discarded aligned RNA-seq reads.
  • Significant alterations in abundance estimates for coding and non-coding RNA were observed.
  • Results were validated using PCR and bedgraph comparisons.

Conclusions:

  • CoCo enhances the accuracy and coverage of RNA expression quantification.
  • The software effectively handles complex transcriptomic data with repetitive and nested genes.
  • CoCo is an open-source tool available for broader research application.