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

Parallel Processing01:20

Parallel Processing

441
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
441
Sanger Sequencing01:57

Sanger Sequencing

766.7K
DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
766.7K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

905
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
905
Sample Preparation for Analysis: Advanced Techniques01:08

Sample Preparation for Analysis: Advanced Techniques

869
Accurate analysis of complex samples often requires advanced preparation techniques to achieve reliable and reproducible results. Samples containing inorganic or organic materials can be challenging to dissolve or decompose effectively. Standard sample preparation methods include acid digestion, fusion, dry ashing, and wet digestion.
Acid digestion with strong acids is commonly used to dissolve inorganic materials that are insoluble (do not dissolve) in water. This method can be useful for...
869
Sample Preparation for Analysis: Overview01:21

Sample Preparation for Analysis: Overview

759
Sample preparation is an essential step in the analytical process. It involves preparing a sample so that it can be analyzed accurately. The goal is to extract the analyte, the substance you want to measure, from the sample while removing any components that may interfere with the analysis. Sample preparation techniques vary depending on the physical state of the sample.
Bulk or large solid samples are typically reduced in size using grinding, crushing, or milling techniques to increase the...
759
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.3K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
18.3K

You might also read

Related Articles

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

Sort by
Same author

b-move: faster lossless approximate pattern matching in a run-length compressed index.

Algorithms for molecular biology : AMB·2025
Same author

Run-length compressed metagenomic read classification with SMEM-finding and tagging.

bioRxiv : the preprint server for biology·2025
Same author

ELLIPSIS: robust quantification of splicing in scRNA-seq.

Bioinformatics (Oxford, England)·2025
Same author

b-move: Faster Lossless Approximate Pattern Matching in a Run-Length Compressed Index.

Research square·2024
Same author

Lossless Approximate Pattern Matching: Automated Design of Efficient Search Schemes.

Journal of computational biology : a journal of computational molecular cell biology·2024
Same author

b-move: faster bidirectional character extensions in a run-length compressed index.

bioRxiv : the preprint server for biology·2024
Same journal

Characterization of genomic diversity in bacteriophages infecting Rhodococcus.

PloS one·2026
Same journal

Effectiveness of the Responding to Experienced and Anticipated Discrimination (READ) training on reducing stigma for medical students in Tunisia.

PloS one·2026
Same journal

Cell-cell junction gene signatures as subtype-specific prognostic biomarkers in breast cancer.

PloS one·2026
Same journal

GC-MS based tentative identification of γ-sitosterol from Brassica nigra seeds and evaluation of its anticancer potential: An integrated in vitro and in silico study.

PloS one·2026
Same journal

Ad-based social media interventions increase belief accuracy and generate pro-social opinions among non-news readers.

PloS one·2026
Same journal

Negotiating knowledge: The role of network hedging in the production of high-impact science.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Nov 18, 2025

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.5K

Multithreaded variant calling in elPrep 5.

Charlotte Herzeel1, Pascal Costanza1, Dries Decap1,2

  • 1ExaScience Life Lab, imec, Leuven, Belgium.

Plos One
|February 4, 2021
PubMed
Summary
This summary is machine-generated.

elPrep 5 accelerates variant calling pipelines by 8-16x, offering identical results to GATK4. This updated framework efficiently processes sequencing alignment/map files for faster genomic data analysis.

More Related Videos

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
08:35

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

6.0K
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

34.3K

Related Experiment Videos

Last Updated: Nov 18, 2025

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.5K
Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
08:35

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

6.0K
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

34.3K

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Variant calling is crucial for genomic analysis.
  • Existing pipelines like GATK Best Practices are computationally intensive.
  • Efficient processing of sequencing alignment/map files is essential.

Purpose of the Study:

  • To present elPrep 5, an updated framework for variant calling.
  • To enable elPrep 5 to execute the full GATK Best Practices pipeline.
  • To significantly reduce runtime while maintaining output identity.

Main Methods:

  • elPrep 5 integrates PCR and optical duplicate marking, coordinate sorting, base quality score recalibration, and haplotype caller variant calling.
  • Parallelization and merging of pipeline steps are employed.
  • Benchmarks were conducted on whole-exome and whole-genome data.

Main Results:

  • elPrep 5 achieves identical BAM and VCF output compared to GATK4.
  • Runtime is reduced by a factor of 8-16x on the same hardware.
  • Significant speed-up is observed for both whole-exome and whole-genome data.

Conclusions:

  • elPrep 5 is a faster alternative to GATK4 for variant calling.
  • The framework offers a drop-in replacement for users needing accelerated genomic data processing.
  • elPrep 5 enhances the efficiency of complex variant calling pipelines.