Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

RNA-seq

RNA-seq

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...

You might also read

Related Articles

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

Sort by

Same author

Genetic and transcriptomic determinants of disseminated coccidioidomycosis identify a founder variant in <i>NLRX1</i> and ancestry-specific rare variants in immune response genes.

medRxiv : the preprint server for health sciences·2026

Same author

Automated implementation of the SwabSeq COVID-19 diagnostic assay on the opentrons flex liquid-handling robot.

Diagnostic microbiology and infectious disease·2026

Same author

Single-cell profiling of DNA methylation in autism spectrum disorder prefrontal cortex reveals distinct regulatory and aging signatures.

Cell genomics·2026

Same author

Systematic evaluation of 24 extraction and library preparation combinations for metagenomic sequencing of SARS-CoV-2 in saliva.

bioRxiv : the preprint server for biology·2026

Same author

A Single-Cell and Spatial 3D Multi-omic Atlas of Developing Human Basal Ganglia and Inhibitory Neurons.

bioRxiv : the preprint server for biology·2026

Same author

A Single-Cell Atlas of DNA Methylation in Autism Spectrum Disorder Reveals Distinct Regulatory and Aging Signatures.

bioRxiv : the preprint server for biology·2025

Search research articles

Related Experiment Video

Updated: May 6, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

eALPS: estimating abundance levels in pooled sequencing using available genotyping data.

Itamar Eskin¹, Farhad Hormozdiari, Lucia Conde

¹1 The Blavatnik School of Computer Science, Tel-Aviv University , Tel Aviv, Israel .

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology

|October 23, 2013

Summary

Accurately estimating DNA sample proportions in pooled sequencing is vital to avoid false discoveries in genetic studies. Our eALPS method uses genotype data to precisely determine these proportions, improving accuracy in population studies and metagenomics.

More Related Videos

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Related Experiment Videos

Last Updated: May 6, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Area of Science:

Genomics
Bioinformatics
Population Genetics

Background:

High-throughput sequencing enables detailed genetic variation analysis.
DNA sequencing often involves pooled samples with unknown individual abundances, common in metagenomics and population studies.
Pooling strategies can reduce costs for large-scale genetic projects, but unknown proportions risk spurious associations.

Purpose of the Study:

To develop a method for accurately estimating sample proportions in pooled DNA sequencing data.
To address the challenge of unknown DNA abundances in pooled sequencing for population genetics and metagenomics.
To validate the method's effectiveness using real-world sequencing data.

Main Methods:

Proposed eALPS (estimated Allele Proportions in Sequencing) method.
Utilized existing genotype data alongside pooled sequence data for proportion estimation.
Developed eALPS-LD for scenarios with incomplete individual genotyping and eALPS-BCR for metagenomic applications.

Main Results:

Demonstrated the critical importance of accurate proportion estimation to prevent false discoveries, using non-Hodgkin's lymphoma data.
Validated eALPS's applicability to metagenomic species quantification, particularly for closely related species.
Showcased eALPS-LD's capability to estimate proportions even with missing genotype data.

Conclusions:

Accurate estimation of sample proportions in pooled sequencing is essential for reliable genetic variation analysis.
The eALPS method provides a robust solution for proportion estimation in population studies and metagenomics.
eALPS enhances the utility of pooled sequencing by mitigating risks of spurious associations and improving metagenomic resolution.